Work-in-Progress Draft Report of the 

Internet of Things (IoT) Advisory Board 

(IoTAB)

February 23, 2024 Pre-Read Draft
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IoT Advisory Board Members

Benson M. Chan (IoT Advisory Board Chair), Chief Operating Officer, Strategy 

of Things Inc.

Daniel W. Caprio Jr. (IoT Advisory Board Vice Chair), Co-founder and Chair, The 

Providence Group

Michael J. Bergman, Vice President, Technology and Standards, Consumer 

Technology Association

Ranveer Chandra, Managing Director of Research for Industry and Chief 

Technology Officer of Agri-Food, Microsoft

Nicholas Emanuel, Head of Product U.S., CropX

Steven E. Griffith, Executive Director, National Electrical Manufacturers 

Association

Tom Katsioulas, Chair, Global Semiconductor Alliance

Kevin T. Kornegay, Professor and IoT Security Endowed Chair, Morgan State 

University

Debra Lam, Managing Director of Smart Cities and Inclusive Innovation, 

Georgia Institute of Technology

Ann Mehra

Robby Moss, President and Principal Consultant, TGL Enterprises LLC

Nicole Raimundo, Chief Information Officer, Town of Cary, North Carolina

Maria Rerecich, Senior Director of Product Testing, Consumer Reports

Debbie A. Reynolds, Founder, Chief Executive Officer and Chief Data Privacy 

Officer, Debbie Reynolds Consulting, LLC

Arman Shehabi, Staff Scientist, Lawrence Berkeley National Laboratory

Peter Tseronis, Founder and Chief Executive Officer, Dots and Bridges LLC

Certain commercial entities, equipment, or materials may be identified in this document in 

order to describe a concept adequately. Such identification is not intended to imply 

recommendation or endorsement, nor is it intended to imply that the entities, materials, or 

equipment are necessarily the best available for the purpose.
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IoT Advisory Board Members ................................................................................................................................ 2

Executive Summary .................................................................................................................................................... 7

Introduction......................................................................................................................................................................8

Background .....................................................................................................................................................................12

IoT Can Transform Business Models...........................................................................................................16

Findings of the IoT Advisory Board................................................................................................................47

General findings ..................................................................................................................................................... 47

Industry findings....................................................................................................................................................48

General Findings – Specific Considerations ........................................................................................49

Industry findings....................................................................................................................................................88

Smart Infrastructure.............................................................................................................................................93

Recommendations of the IoT Advisory Board.....................................................................................108

Recommendations Summary ......................................................................................................................110

Establishing a National IoT Strategy and Leadership........................................................................111

Key Recommendation KR1.1: The IoTAB recommends a strategic national approach 

for taking full advantage of the opportunity presented by the IoT. ....................................111

Small Business Leadership.............................................................................................................................119

Key Recommendation KR1.2: The government should accelerate IoT technology 

adoption as well as manufacturing for small businesses and startup organizations. 

This can be done via policies, procedures, and funding methods that specifically 

target them. ..............................................................................................................................................................119

International Leadership.................................................................................................................................123

Key Recommendation KR1.3: The government should promote international 

collaboration in IoT adoption across global supply chains to share knowledge, best 

practices, and resources. .................................................................................................................................123

Modernizing IoT Infrastructure........................................................................................................................125

Equitable and Responsible Data Sharing............................................................................................125

Key Recommendation KR2.1: The government should foster policies that encourage 

responsible and equitable sharing of IoT data and thereby drive economic growth, 

societal benefits, and sustainability. ........................................................................................................125

Consistent and Resilient Interoperability ............................................................................................128

Key Recommendation KR2.2: The government should establish methods to foster 

interoperability for IoT technology, including through the use of consistent models, 

protocols, application interfaces, and schemas. .............................................................................128
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Promoting Existing Methods .......................................................................................................................132

Key Recommendation KR2.3: The government should promote collaborative 

development across industries to adopt existing industry standards and protocols.

...........................................................................................................................................................................................132

Key Recommendation KR2.4: The federal government should expand and improve 

programs that ensure sufficient availability, reliablility and connectivity for IoT in all 

areas of the country. ..........................................................................................................................................136

Establish Trust in IoT ................................................................................................................................................141

Cybersecurity Improvement..........................................................................................................................141

Key Recommendation KR3.1: The Federal Government should provide specific and 

consistent cybersecurity guidance for IoT providers and adopters to ensure secure 

operations in a whole-of-government approach. ...........................................................................141

Data Privacy Regulation..................................................................................................................................147

Key Recommendation KR3.2: Congress should pass comprehensive federal privacy 

legislation...................................................................................................................................................................147

Data and Privacy Policy...................................................................................................................................148

Key Recommendation KR3.3: The White House and Congress should 

facilitate/support the development of a Data and Privacy Policy Framework.........148

Privacy Protections and Transparency for IoT..................................................................................153

Fostering an IoT-Ready Workforce...............................................................................................................159

Key Recommendation KR4.1: The government should invest in and promote IoTrelated aspects of education and workforce. ...................................................................................166

Government Support to Facilitate Industry Adoption of IoT ......................................................172

Leverage Federal Grants And Programs To Improve IoT Technology Use...................172

Key Recommendation KR5.1: The government should consider new financial 

models for sustaining and supporting programs when considering IoT project 

feasibility.....................................................................................................................................................................172

Leading the Way for IoT Adoption in Agriculture..........................................................................174

Key Recommendation KR5.2: The government should develop a comprehensive 

strategy for agricultural IoT. ..........................................................................................................................174

Leading the Way for IoT Adoption Through Smart Cities .......................................................180

Key Recommendation KR5.3: The government should implement specific actions to 

further promote IoT adoption through smart cities. ..................................................................180

Leading the Way for IoT Adoption for Public Safety....................................................................186
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Key Recommendation KR5.4: The government should implement specific actions 

to promote IoT adoption that will improve public safety. ........................................................186

Leading the Way for IoT Adoption for Health Care...................................................................... 190

Key Recommendation KR5.5: The government should implement specific actions to 

promote IoT adoption in the health care industry.]..................................................................... 190

Sustainability / Environmental Monitoring........................................................................................ 194

Key Recommendation KR5.6: The government should implement specific actions 

to promote IoT adoption that will improve sustainability and environmental 

monitoring. .............................................................................................................................................................. 194

Smart Transportation.........................................................................................................................................201

Key Recommendation KR5.7: The government should implement specific actions to 

promote IoT adoption in Smart Transit and Transportation. .................................................201

Facilitating an IoT-enabled Economy........................................................................................................202

Key Recommendation KR6.1: The government should monitor and evaluate 

progress of IoT adoption for supply chain logistics......................................................................203

Public and Private Partnership................................................................................................................. 204

Key Recommendation KR6.2: The government should help establish and foster 

public-private partnerships (PPPs) focused on IoT adoption to facilitate 

collaboration and knowledge sharing between government agencies, businesses, 

technology providers, and academia. .................................................................................................. 204

Key Recommendation KR6.3: The government should support trusted architectures 

and conduct a limited pilot to assess the value of trusted digital threads for 

provenance and traceability across the supply chain.................................................................159

Key Recommendation KR6.4: The government should actively promote and 

support the adoption of Generative AI applications for agricultural IoT, with the aim 

of improving decision-making, optimizing resource utilization, and enhancing 

productivity in the agricultural sector through innovative and data-driven solutions.

......................................................................................................................................................................................... 209

Conclusion ................................................................................................................................................................... 209

References .....................................................................................................................................................................212

Acknowledgements................................................................................................................................................212

Appendices....................................................................................................................................................................213

Appendix A: IoT Stakeholders ......................................................................................................................213

Appendix B: Leveraging U.S.-EU CHIPS Acts and IoT for Cross-Border Supply Chain 

Traceability to Strengthen National and Economic Security.................................................219
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Table of Abbreviations ..........................................................................................................................................225

Compliance Matrix ..................................................................................................................................................229
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Executive Summary

[this will be drafted after other sections are complete]
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Introduction

The United States is undergoing a profound transformation - one that is driven by 

economic, societal, technological, and cultural innovations brought about by the 

advancement of the Internet of Things (IoT). This fourth industrial revolution 

intertwines connectivity and digital innovation with the opportunity to drive a 

revolutionary transformation across our nation. 

We begin with three different stories all illustrating a possible future glimpse into 

industry sectors that could be radically transformed by the evolution of Internet of 

Things (IoT) technologies today. These stories offer glimpses into a future transformed 

by the IoT - a future where agriculture thrives in harmony with nature, supply chains 

operate with unimaginable efficiency, public safety is bolstered by intelligent systems, 

transportation flows seamlessly through smart cities, and healthcare becomes 

personalized and preventive.

These stories are illustrative yet showcase the scale of today’s technologies into a 

vastly transformative edge for the benefit of our society tomorrow. We then peer into 

the impacts of such transformations and the incredible areas of US economic 

prosperity such advancements could provide our future nation for all Americans.

Future Glimpse into Agriculture and Environmental Monitoring

The year is 2060. A rural farmer in the Midwest of the US stands amidst her thriving 

fields, despite the local effects of climate change over the last decade. This is a 

seemingly testament to the transformative power provided by the advancement of 

IoT in agriculture over the last few decades. Gone are the days of mostly manual labor 

and unpredictable weather without efficiency to risk management. 

Invisible sensors provide real time inputs about the soil on moisture levels, nutrient 

composition, and the balance of microbial life. Drones, no longer mere tools of 

observation, scatter across farm sky, equipped with advanced bio-scanners that 

identify potential threats and optimize resource allocation with pinpoint accuracy. 

Self-driving tractors zig zag across the field in full automation guided by AI algorithms 

that orchestrate every aspect of the farm with meticulous precision. This is not just a 

farm; it's a living laboratory, a model of sustainability that thrives in harmony with the 

natural world.

Looking back from today, how do we embrace the evolution of today's early-stage IoT 

technology like sensors and drones to achieve this tomorrow land farm? The 

widespread adoption might come slow at first but then with accelerating possibility 

given the proliferation of affordable sensors across every aspect of farm operations, 

the rise of robust data networks to enable seamless communication and remote 
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monitoring, and the convergence of data driven decisions from AI automating 

outcomes in real time. These technologies, once seen as mere concepts, are poised to 

revolutionize the way we grow our food and bring food to the table from farms, 

making the supply chain itself more sustainable, efficient, and personalized. 

Future Glimpse into Public Safety and Smart Transit

The year is 2065. An urban officer patrols the streets of the large metropolitan city 

where public safety and smart traffic are more autonomous to the interconnected 

nature of technology. Gone are the days of slow response times, limited situational 

awareness, and unpredictable traffic patterns. In their place, a network of intelligent 

sensors and AI algorithms work tirelessly to keep the city safe and flowing smoothly.

Embedded sensors embedded in roadways monitor traffic flow in real-time, 

automatically adjusting traffic signals and optimizing routes to minimize congestion. 

Smart cameras and drones alert law enforcement towards suspicious activity and 

traffic incidents in real time. The live feeds from nearby cameras and other IoT devices 

can even communicate directly within a larger ecosystem and give coordinated 

responses to law enforcement and public safety organizations in the vicinity. 

Today, a fire has erupted in a high-rise apartment building, trapping residents on the 

upper floors. The building itself is encased with smart technology. Sensors within the 

building detect the blaze, automatically activating its integrated fire suppression 

system and activating sprinklers. Drones equipped with heat sensors arrive to the 

building and scan for trapped individuals to guide firefighters to their location. 

Additionally, all law enforcement and public safety personnel have on their advanced 

smart suits with their own sensors for their localized vicinity and as they join together 

they receive in unison real-time data on the fire's location, the location of the trapped 

individuals and each other, and the actions currently underway from all parties 

displayed on their artificial reality displays embedded in their helmets and 

information in their earpieces.

Looking back from today, the transformation of today’s skyline seems like science 

fiction. Yet, it was built upon the proliferation of today’s low-cost sensors across city 

and traffic ecosystems, the converge of hyperconnected IoT ecosystems of different 

types of devices monitoring different types of data processed by AI algorithms for 

automated real time responses. These technologies, once seen as futuristic concepts, 

have now become the backbone of a safe, efficient, and sustainable city, fostering 

unprecedented levels of security and mobility.
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Future Glimpse into Healthcare and Medicine

The year is 2070. A doctor interacts with a holographic display, analyzing real-time 

data flowing from her patients' embedded biosensors. Strides in technology have 

empowered healthcare professionals to see the unseen, intervene before the 

symptoms, and personalize medicine with unparalleled precision. 

Biosensors are tiny, intelligent devices that continuously monitor vital signs, blood 

sugar levels, and even hormonal balances, providing a real-time snapshot of individual 

health. Microscopic pressure sensors embedded in the heart monitor its function and

rhythm, detecting potential issues before they manifest as symptoms. Bio-implants 

in the brain track neurotransmitter activity, offering insights into mental well-being, 

sleeping patterns, and personalized interventions for anxiety, depression, and agerelated issues like cognitive decline.

Predictive algorithms flag potential health concerns before they even manifest, 

allowing for preventative measures and early interventions into what were once 

considered chronic illnesses. In-home robots assist with medication adherence and 

provide personalized care instructions, empowering patients to manage their own 

health more effectively with optimism lessening the strain on the medical field to 

more serious issues for physical doctor office visits. These same data streams if 

consented provide real-time data feeds to researchers in the medical field looking to 

run at scale optimized AI algorithms and models to spin studies on predictive 

treatment protocols and insights for pharmaceutical companies to develop new 

classes of drugs, both at scale.

Looking back from today, the early stages of IoT devices like wearables and sensors, 

coupled with the rapid advancement of AI and data analytics, and the evolutionary 

integration of embedded biosensors enable human-machine interaction evolution to 

healthcare delivery. These technologies, once in their infancy, have now woven 

themselves into the very fabric of healthcare, transforming it from a reactive system 

to a proactive and preventative field at scale.

Areas of US Economic Prosperity

While these scenarios still seem futuristic, they are based on outcomes that are 

possible by integrating IoT technologies into our everyday infrastructure. However, 

today’s IoT technology has not yet reached its pinnacle of potential nor are its benefits 

realized at scale. We recognize three impacts to be made:

• There must be a broader national vision to enable a more resilient nation with 

advanced technological capabilities to provide economic prosperity to 

Americans. 
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• There must be continued research and funding into these IoT technologies and 

their applications across market sectors to innovate into tomorrow’s nation and 

societal benefits. 

• There must be a collective action and a nationwide public and private 

commitment to bridge the gap between the present and a promising future. 

In our global ecosystem, all developed nations seek these same advantages. 

Consequently, the adoption of IoT is not just an option, it is an imperative for the 

United States. It is a call to action to embrace a future where connectivity transcends 

boundaries, propelling our economy to new heights, fostering societal well-being, and 

ensuring that America remains at the forefront of global innovation.

Despite the unlimited potential and benefits of this transformation, a number of 

significant challenges and barriers stand in the way. It is imperative that we embrace 

the potential of IoT, acknowledge and overcome the challenges, and act with 

deliberation and urgency to realize its benefits for our economy and society. We must 

act with the same characteristics that built our nation - lead with vision and 

innovation, execute with passion and relentless tenacity, and persevere with 

unwavering commitment for the betterment of all Americans.

This report contains our findings and groups actionable recommendations under 

overarching themes that serve to guide the US towards an IoT-empowered future. 

This includes experiences and perspectives from a cross-section of industry, local 

government, academia and other private-sector experts. We urge the Federal 

Working Group to study our recommendations and adopt those that will best serve 

the needs of this nation.
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Background 

In January 2020, Congress enacted the William M. (Mac) Thornberry National Defense 

Authorization Act for Fiscal Year 2021 (Public Law No. 116-283). Section 9204(b)(5) of 

this act established the Internet of Things Advisory Board (IoTAB) within the 

Department of Commerce. In accordance with the Federal Advisory Committee Act, 

as amended, 5 U.S.C., App., the IoT Advisory Board (IoTAB) was chartered in December 

2021. 

The IoTAB is chartered to provide advice to the Internet of Things Federal Working 

Group (IoTFWG). Specifically, this charter requires the following: 

4. Description of Duties. The Board shall advise the Working Group with respect to --

a. the identification of any Federal regulations, statutes, grant practices, 

programs, budgetary or jurisdictional challenges, and other sector-specific policies 

that are inhibiting, or could inhibit, the development of the Internet of Things;

b. situations in which the use of the Internet of Things is likely to deliver significant 

and scalable economic and societal benefits to the United States, including benefits 

from 

or to— 

i. smart traffic and transit technologies; 

ii. augmented logistics and supply chains;

iii. sustainable infrastructure; 

iv. precision agriculture;

v. environmental monitoring;

vi. public safety; and 

vii. health care;

c. whether adequate spectrum is available to support the growing Internet of 

Things and 

what legal or regulatory barriers may exist to providing any spectrum needed in the 

future;

d. policies, programs, or multi-stakeholder activities that— 

i. promote or are related to the privacy of individuals who use or are 

affected 

by the Internet of Things;
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ii. may enhance the security of the Internet of Things, including the 

security 

of critical infrastructure;

iii. may protect users of the Internet of Things; and

iv. may encourage coordination among Federal agencies with jurisdiction 

over the Internet of Things;

e. the opportunities and challenges associated with the use of Internet of Things 

technology by small businesses; and

f. any international proceeding, international negotiation, or other international 

matter affecting the Internet of Things to which the United States is or should be a 

party.

In addition, the charter provides for the following:

• The Board will submit to the Internet of Things Working Group a report that 

includes any of its findings or recommendations. The report will be 

administratively delivered to the Internet of Things Working Group through 

the Director of the National Institute of Standards and Technology (NIST).

• The Board shall set its own agenda in carrying out its duties. The Working 

Group may suggest topics or items for the Board to study, and the Board 

shall take those suggestions into consideration in carrying out its duties.

• The Board will function solely as an advisory body, in accordance with the 

provisions of FACA.

• The membership of the IoTAB consists of sixteen members (listed on the 

internal cover). The Secretary of Commerce appointed all members of the 

IoTAB and the Board has met on a regular schedule as necessary to complete 

the report.
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Introduction to the Internet of Things

The Internet of Things (IoT) is composed of devices embedded with sensors and 

actuators that are connected to the internet to react to and influence physical actions 

in the real world. As a result, the IoT can be seen as a collection of disparate 

technologies that work together to create innovative outcomes. 

From a technology perspective, IoT have sensors that collect real world data and 

actuators that perform actions in the physical environment based on the processing 

of the data collected. IoT data is either processed locally on the device, by an onpremises processor, or sent over the internet to be handled off-premises. For example, 

simple commands for a device's physical actions, such as “increase temperature” or 

“unlock the door,” may be generated locally or sent down from the central processing. 

A high level IoT technical architecture is shown below in Figure 1. 

Fig. 1 - High Level Internet of Things Architecture
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From an economic perspective, adding sensors and actuators to the internet yields 

value from doing old things in new ways and seeing new things done in ways that 

were not possible before. 

Figure 2 below shows an example of how this is possible with the example of a product 

manufacturing process enhanced by IoT. 

Figure 1: IoT Example: IoT-Enhanced Manufacturing Process and Resulting 

Opportunities

Prior to IoT, equipment dealers traditionally sold machinery, spare parts, warranties, 

maintenance contracts and installation and repair services. 

The addition of IoT to the equipment creates new capabilities and value for both 

buyers and dealers. These “smart machines” allow dealers to offer new services and 

existing services in new ways. For example, onboard IoT sensors allow a dealer’s 

technicians to monitor and diagnose their customers’ machinery remotely and avoid 

an onsite visit. Predictive algorithms driven by IoT sensor data alert technicians when 

maintenance and repairs are needed, order a replacement part and then schedule a 

technician to replace the part. This helps the customer avoid unplanned machinery 

downtime and maintain operational productivity. 

At the same time the IoT sensors collect large amounts of data, including machinery 

usage data from its entire customer base which is aggregated by the manufacturer 

to understand how their machines are used. This information is analyzed by company 

engineers to create new services and applications that are sold to the customers. For 
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example, the information can be used to create performance optimization software 

and consulting services. Customers purchase these new information products and 

services because it further enhances their operational productivity, reduces 

inefficiencies and enables them to take on larger jobs.

For example, in a manufacturing context, the data and insights collected from “smart 

machines” can be aggregated, packaged and sold to lubricant vendors, who use the 

information to create more effective premium formulations. The data can also be 

purchased by insurance companies who use it in a way that minimizes on-the-job 

accidents. Consultants use the same data to help the factories plan and implement 

operational process improvements. 

Finally, “smart machines” provide factories with the capability to create innovative 

new businesses, such as “Manufacturing as a Service”. With full visibility into the actual 

utilization of their production equipment, factories can offer excess capacities and 

capabilities to customers. The “uberization” of factories turns manufacturers into 

“manufacturing utilities” to offer contract manufacturing at agilities, scales and 

efficiencies unmatched by traditional factories.

This simple example highlights some of the value offered by IoT. In general, IoT offers 

the potential to transform business models. It does this by transforming product 

economics, business models and the business ecosystems that IoT is offered in.

IoT Can Transform Business Models

[Note: this is some content inserted from Tom’s findings/edits. There may be some 

duplication, but Tom’s content has a lot of detail, some of which can substitute and/or 

complement some of the content above. It is placed here for editor review and 

possible use. I think we can use his content to answer the question What can or does 

IoT do?]

IoT connectivity changes product economics. To take advantage of the IoT potential, 

product suppliers must transform their business to become smart-connected 

product suppliers enabling new services models and revenue streams. 

The 2021 McKinsey report classification of IoT Applications as “settings” (or 

environments) indicates that IoT vertical markets should be considered in the broader 

context of connectivity among smart cities, critical infrastructure, and supply 

chains. From an IoT edge use case perspective, the types of enterprises and personas 

dealing with IoT use cases vary across various vertical markets that serve these 

environments. 
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For example, in Industrial IoT connected devices and process sensors are managed 

by information technology (IT) and operational technology (OT) professionals. In 

Consumer IoT connected devices with embedded sensors are managed by users or 

device makers. And in Enterprise IoT, connected devices in data centers are 

exclusively managed by IT professionals. 

Connectivity creates opportunities for product suppliers to change their mindset 

about growing their business. Instead of viewing their business as being suppliers of 

smart-connected products, IoT leaders view their business as being smart-connected 

suppliers to their customers using their products. Being a connected supplier, 

provides several benefits:

1. High Visibility on Product Field Use: IoT connectivity provides real-time 

insights into how customers use products, allowing suppliers to gather 

valuable data on usage patterns, performance, and potential issues.

2. Remote Lifecycle Management: Over-the-Air (OTA) updates enables remote 

management of devices and software, allowing suppliers to deliver 

improvements, security patches, and new features without physical 

intervention.

3. Reduced Support Costs and RMAs: IoT-connected devices enable proactive 

issue detection and troubleshooting, reducing the need for customer support 

and costly returns Return Merchandise Authorizations (RMAs).

4. Lower OPEX, Higher Differentiation: Operational expenses (OPEX) can be 

minimized as suppliers gain greater control over product performance and 

maintenance. Moreover, IoT capabilities help them differentiate products and 

increase market share.
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5. Hardware as a Service1 Business Model: IoT facilitates the introduction of new 

revenue streams through subscription-based models, offering services like 

remote monitoring, predictive maintenance, and data analytics as value-added 

services.

IoT Can Transform Business Ecosystems

[This section below also came from Tom’s findings edits. This section is more visionary, 

and we should have some statement saying this is one possible, but speculative and 

visionary view of where IoT can take the economy.}

Finding: Connectivity changes product-based businesses to platform-based 

businesses with smart-connected products and ecosystem partners delivering 

higher value end-to-end solutions compared to individual parts sold separately. 

Connectivity changes products and businesses by enabling the evolution of solutions 

and partner ecosystems. Technology adoption rates vary based on vertical market 

sophistication and ability of enterprises to embrace new technologies and “Cross the 

Chasm2

” that creates new markets (Innovators, to Early Adopters, Early Majority, Late 

Majority, Laggards). 

Connectivity accelerates adoption of IoT. Smart, connected products reshape 

competition within industries and expand industry boundaries. The basis of 

competition shifts from discrete products to product systems to systems of systems, 

to platform ecosystems and marketplaces3

. 

1 Deloitte - https://www.linkedin.com/pulse/unlock-limitless-possibilities-empower-your-customers-rochak-sethi/ 2 https://en.wikipedia.org/wiki/Crossing_the_Chasm 3 https://hbr.org/2014/11/how-smart-connected-products-are-transforming-competition 
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Businesses evolve products into platforms by combining existing products with 

technologies from other suppliers and forming partnerships for end-to-end solutions. 

Complex system-of-systems and solutions require collaboration and business 

connectivity platforms that incentivize businesses to participate and share the 

innovation burden and economic value delivered.

Smart-connected product businesses evolve into solutions platforms. The 

similarities of how connected product businesses evolve into platform businesses are 

striking. Just replace the tractor with a plane, and the peripheral capabilities follow 

the same principles. Only the application software changes and partnerships with 

application experts accelerate adoption. Companies that deliver smart-connected 

solutions with ecosystem partners capture high value. 

Companies whose product platforms connect to other systems will capture more 

value with ecosystem partnerships by expanding industry boundaries. For example, 

a coordinated approach across supply chains in transportation and logistics 

ecosystems will speed adoption, across connected industries accelerate supply chain 

resilience and enable new solutions.

IoT connectivity drives business transformation for continuous improvements to 

deliver customer benefits, increase retention, boost differentiation, manage 

complexity and creating higher value and economies of scale with ecosystem 

partners.

Specific Applications of IoT

There are several specific applications of the IoT. Each application has its own unique 

set of use cases, benefits and challenges. This section will highlight a few in greater 

detail.

IoT for the Consumer 

Internet of Things (IoT) technology is becoming increasingly prevalent in consumer 

products, from smart TVs and wearable devices (fitness trackers, smartwatches), to 

products that are typically not thought of as “consumer electronics”, such as 

refrigerators and door locks. These “smart” products connect to the internet and used 

data create new functionality and enhance existing features and functions to create 

benefits to consumers in new and better ways. Adoption can bring many benefits to 

the consumer in many areas, such as:

● Convenience: Tracking tags attached to keys, purses and luggage, help locate 

and recover lost items no matter where they are. Smart appliances can be 

monitored and operated remotely, allowing consumers to control them from 
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anywhere and anytime. Smart refrigerators monitor grocery quantities, and 

create weekly shopping lists.

● Safety: Connected baby monitors and security cameras monitor activity to 

protect people in and around the home. Smart doorbells and smart door locks 

prevent unauthorized access to homes. Security systems, integrated with 

cameras, monitors, smart doorbells and locks, are connected with call centers 

to protect the physical safety of residents. 

● Maintenance/Monitoring: Connected devices can report on their own status, 

such as an air purifier alerting of the need for a filter change. They can monitor 

conditions; for example, a smart water leak detector senses water flow through 

pipes and can send an alert for even small water leaks.

● Cost Savings: Smart irrigation controllers can incorporate data about weather 

conditions and sensor inputs on soil moisture, to optimize the frequency and 

amount of lawn watering. Connected thermostats monitor and maintain home 

temperatures while minimizing energy usage.

● Health: Wearable devices such as fitness trackers and smartwatches 

encourage users to track their health data and increase their physical activity, 

often “game-ifying” the experience to promote regular use. Other connected 

devices such as body scales, blood pressure monitors, and CPAP machines 

allow consumers to see trends in their data, improve compliance, and 

optionally report back to the health provider.

● Entertainment: Consumers stream a wide selection of video and audio content 

on their smart TVs and wireless speakers, and connected cameras inside the 

home can provide hours of entertainment watching and interacting with 

house pets remotely.

Despite these potential benefits, IoT is uncharted territory for many consumers. The 

connected nature of IoT products, the collection of data, and subscription pricing 

present challenges for the consumer:

● Cybersecurity: The number of devices connected to a home network increases 

the potential cyber-attack surfaces, and as a result, the security of the home 

router and of all the devices connected to the network becomes a critical link. 

There are particular concerns around child safety, such as intruders on baby 

monitors or smart speakers.

● Privacy: IoT devices collect sensitive and non-sensitive user data. IoT device 

cybersecurity vulnerabilities may allow this data to be accessed by cyber-
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criminals. The collected data may also be used by product manufacturers and 

other third parties in an undisclosed or unauthorized manner, or in a manner 

that may lead to adverse outcomes for the consumer. 

● Usability: Not all consumers are technically or digitally tech-savvy, and many 

current IoT products are difficult to set up, use, troubleshoot and maintain 

without technical knowledge. In some cases, the user experience and user 

interfaces are not intuitive, making the product hard to use and realize benefits 

from.

● Subscription pricing: Consumers are accustomed to buying a product and 

paying once. Some IoT products offer a limited set of features that is available 

on a one-time purchase price, while other features are only available on a 

subscription basis. 

Making a traditional “dumb” product “smart”, such as a door lock, adds complexity, 

risk and cost to a product that consumers possibly felt “was working well before”. 

Robust adoption and realization of its associated benefits will depend on consumer 

understanding, trust and perception of value of IoT. Continued efforts by industry and 

government to support initiatives, such as the U.S. Cyber Trust Mark labeling, help to

alleviate consumer concerns and facilitate adoption.

IoT in the Smart Home

Today’s homes are becoming increasingly digital and connected. Digital networks 

and telecommunications systems join HVAC (heating, ventilation and air 

conditioning), plumbing, and electrical systems as essential infrastructure of a 

functioning home. Broadband Internet connects these homes with a variety of 

services, including news, entertainment, business and government services, 

education, and healthcare.

The connected home contains a variety of disparate digital systems, including 

audio/video (television, receivers, DVD players, media servers, etc.), security and access 

(alarms, cameras, electronic doorbells, digital door locks, etc.), HVAC (thermostats, 

fans, etc.), energy management, and automation (lighting, windows, blinds, garage 

doors, irrigation, etc.). These systems operate as individual systems, and sometimes in 

an orchestrated fashion through a central home control and automation system.

IoT adds intelligence to this connected home in multiple ways. Sensors monitor a 

variety of conditions around the home, while the data collected is routed to a cloud 

data center and analyzed by software algorithms to create optimized responses. 

Homeowners can access the information and interact with the home remotely 
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through a website or a mobile app. IoT-enabled home systems provide significant 

improvements in energy efficiency, occupant comfort, security, and other functions. 

Smart home technology is diverse. The capabilities of IoT-connected products for a 

smart home can generally be classified into four main functions: monitor, control, 

optimize, and automate. Some smart home applications perform one function, while 

others do more. 

The potential benefits include greater comfort, convenience and security with 

reduced energy consumption. Other benefits include:

• Increased awareness of home condition and activities through monitoring. 

IoT-connected devices monitor the condition of a home and inform the 

occupant of abnormal conditions or take appropriate automated responsive 

actions. For example, pool safety is a concern for families with young children. 

Connected video cameras monitor the swimming pool, alerting residents to 

unaccompanied children entering the restricted area. Another important 

smart home application is the use of IoT to monitor the health and safety of 

elderly residents living alone. In-room microphones detect the sound of falls or 

cries for help, notifying family members and caregivers. In-room proximity 

sensors paired with algorithms monitor resident movements throughout the 

home, and alert caregivers of unusual patterns of activity or inactivity. Another 

common smart home IoT application is an outdoor air quality monitor. These 

monitors detect the pollution levels of the outside air and share that 

information on a website. This allows the community to understand the current 

air quality and take the necessary precautions, such as staying indoors or 

refraining from heavy physical activity.

• Remote access, control and autonomous operation. The connected nature 

of IoT technologies allows users to remotely control and operate smart home 

devices and equipment. For example, a resident can unlock a smart door lock 

remotely to allow a guest into the home. A resident can turn house lights on 

and off through a control panel in the home, or remotely through a mobile 

phone app. Smart home applications can be controlled manually, or 

autonomously in response to pre-set threshold conditions or intelligent 

algorithms that learns from specific patterns in data. A smart irrigation system 

turns off the garden sprinklers when it senses rain or delays operation if soil 

moisture levels are high. A IoT-enabled HVAC system automatically resets to 

lower setpoints when it senses no occupants at home. 

• Optimize home operations through intelligence. The use of data collected 

from IoT connected devices have made homes more livable, safer, convenient, 
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and economical to maintain. Algorithms analyze the data to optimize the use 

of home systems. For example, smart HVAC systems can be optimized based 

on patterns of use, automatically turning on thirty minutes in the morning 

before first activity and turning off thirty minutes before occupants go to bed, 

based on historical data. Similarly, a home with a solar panel and battery system 

optimizes the mix of electricity stored, discharged to the grid, and used by the 

home users based on past data.

• Automate functions to increase convenience and simplify tasks. Home 

automation platforms integrate various systems together, such as lighting, 

energy management, blinds, audio video, IoT-enabled systems (appliances, 

thermostats, etc.) and others. This integration enables the various systems to 

orchestrate and work together. Combining monitoring, control, and 

optimization capabilities permits home systems to operate autonomously with 

little human input. For example, smart home algorithms know when occupants 

return each day, and what rooms they used in the house. Sensors detect the 

resident’s car entering the driveway and initiates an automated sequence to 

open the garage door, turn on the lights in the areas of the house used by the 

resident, turn on the HVAC systems, turn on the oven, and turn on the television 

system to the right channel. As the evening progresses, lights in the sleeping 

portions of the home are turned on while the common areas are turned down. 

Select appliances, such as the dishwasher and the laundry appliances activate 

at midnight when the electricity rates are the lowest.

While smart home technologies provide a variety of benefits to residents and 

homeowners, there are some challenges to using these technologies. These include:

Interoperability. Modern homes are comprised of a variety of mechanical and 

electrical systems, electronics, appliances, and other equipment. While any single 

system can be optimized to improve efficiency or reduce operating costs, the real 

value is when these individual systems are linked together, combined with sensor and 

external data sources, and then managed as an integrated system. The lack of 

interoperability between the different systems, as well as similar systems from 

different vendors, hinders integration and data sharing. Further complicating matters 

are competing smart home standards that make operating all the IoT connected 

devices challenging. Recent industry collaboration has resulted in the Matter 

standard. While the Matter 1.0 standard officially launched in 2022 and promises the 

potential for interoperability between various smart home devices, there are still many 

existing devices and systems in the market that are not interoperable and compatible.

• Privacy. Smart home technologies collect a lot of information that may be 

private to a resident. For example, the collected data may contain both 
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personally identifiable information (PII) as well non-PII information. While some 

data collection is unavoidable in order to offer personalized and relevant 

experiences and outcomes, smart home users are concerned with how that 

data is used, stored, and secured, as well as who has access to it.

• Cybersecurity. Smart home technologies create new vulnerabilities and attack 

surfaces in the home network. While home networks are smaller and simpler 

compared to their enterprise network counterparts, they are also less secure. 

Enterprise networks are well maintained and updated frequently. In contrast, 

home networks are seldom updated, configured correctly, and maintained. The 

integration of IoT devices into this network greatly increases cybersecurity risks. 

Cybercriminals can penetrate these networks through vulnerable IoT devices 

and gain access to sensitive homeowner information, as well as plant malware 

into the devices and network. In other cases, cybercriminals can access IoT 

devices and intercept the data streams, such as a video feed from a camera

system.

• Subscription Plans. Many smart home technologies are offered as a hardware 

purchase and a subscription service. For example, one manufacturer sells a 

smart doorbell and an accompanying subscription service to access stored 

video. Because IoT and smart home technologies collect a lot of data, storing 

growing amounts of data over a period of time is expensive. Many 

manufacturers, especially smaller ones, are unable to “absorb” that cost and 

must pass it on to the consumer and homeowner. In other cases, smart home 

technology manufacturers offer “premium” features on a subscription basis. 

While there may be justification for these subscription costs, buyers are 

accustomed to paying once and feel that they are “nickel and dimed” by these 

subscription services. 

• User Experience. Smart home and IoT technologies offer benefits to its buyers, 

but those benefits may not be equally accessible to all. Complex configuration 

and setup processes hinder less sophisticated owners and require 3rd party 

installers. It may lead to improperly configured devices that function poorly. In 

addition, some devices are poorly designed with little thought for user 

experience. These poorly designed user interfaces (UI) and experiences (UX) 

discourage users with limited digital literacy from fully accessing and using the 

technology to its fullest. For example, smart home technologies that are 

controlled by voice commands can be challenging. The commands must follow 

a specified format and not in a “natural language” and have trouble accurately 

recognizing accents.
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• Maintenance and Upgrades. Smart home technologies must be maintained 

and updated frequently to stay current, secure and functional. However, some 

users are hesitant to do so because in an integrated smart home, software 

upgrades to one component in a system may “break” the integration with other 

components in the same system or other systems. Repair of this breakage may 

require reconfiguring of select components in the system and are beyond the 

capabilities of most users. These “breaks” are more likely between components 

from different brands. Not all upgrades are performed “over the air” as some 

must be done in-person. These “truck rolls” are expensive and may hinder 

upgrading firmware.

IoT in the Industrial Sector 

Industrial operations are heavily monitored and controlled in a variety of industries, 

including energy mining, chemicals, and transportation These technologies are also 

prevalent in manufacturing, monitoring, process control and operations, and supply 

chain management. Many equipment manufacturers use Industrial Control Systems, 

(ICS), that are used to control processes like manufacturing, product handling, 

production, and distribution. ICS includes Supervisory Control and Data Acquisition 

(SCADA) systems, distributed control systems, and programmable logic controllers 

that incorporate IoT technologies. These technologies are often also referred to 

Operational Technologies (OT). OT is comprised of hardware and software that 

detects or causes a physical change through the direct monitoring and/or control of 

industrial equipment.4 OT devices are as distinct from ‘consumer IoT’ due to their 

usage in commercial operations and are not available or readily available for sale to 

the public.

IoT systems are used in conjunction with existing OT systems to enhance and improve 

operations. For examples, IoT brings sensors, data storage and integration, data 

analytics, and machine learning, can be applied to SCADA systems to improve 

interoperability and coordination among different machines. The sensors collect new 

data from various equipment and continuously feed the data into the analytics. This 

way, machine learning algorithms can learn from past data and fine-tune the settings 

on different machines for thousands or even millions of cycles to reach the optimal 

point of the entire system. Harnessing IoT in industrial markets brings several 

benefits: 

1. Increased efficiency in manufacturing operations. IoT gives manufacturers 

and industrial operators the ability to automate and optimize their operating 

equipment efficiency and/or utilization. The use of robotics and automated 

4 Wikipedia https://en.wikipedia.org/wiki/Operational_technology
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machinery can boost productivity and help manufacturers streamline 

productions, reducing unplanned equipment downtime. Using sensors, 

manufacturers and utilities gain valuable insight into operational performance 

of pieces of equipment as well as entire systems.

2. Reduction of errors. Through digitalization, manufacturers can reduce 

operational and manufacturing errors generally associated with manual labor. 

IoT can help reduce errors in operations, even in those operations that are 

automated like in continuous manufacturing operations. For example, IoT 

sensors can detect anomalies and/or variabilities in a chemical processing 

operation and adjust certain parameters to reduce process waste and increase 

yields. AI and machine learning can do much of the required computing and 

data analysis and make subsequent predictive recommendations which can 

improve a manufacturing process.

3. Predictive maintenance. IoT technologies can alleviate issues and unplanned 

machine downtime associated with reactive maintenance. By monitoring 

equipment performance consistently, industrial operators are able to identify 

issues before they occur and allows them to schedule maintenance prior to any 

downtime.

4. Improved safety. A fully functioning manufacturing operation that 

incorporates sensors and other IoT technologies can use the collected data to 

bolster worker and product safety. Integrated systems can protect workers by 

providing alerts which could automatically and safely cease operations if an 

accident is predicted or until an incident is resolved. Safety can be improved 

with sensors monitoring hazardous conditions and sending alerts when 

necessary, such as detecting chemical leaks or equipment malfunctions, 

reducing the risk of accidents.

5. Cost reduction. The data provided to manufacturers through Industrial IoT 

technologies is giving them the knowledge and tools to reduce costs and 

increase marginal revenue. By using data-driven insights into operations, 

production, marketing, and sales manufacturers can steer their business into a 

more profitable direction.

6. Enhanced Productivity & Quality: IoT technologies can improve productivity 

by providing workers with real-time data and insights. Continuous monitoring 

of product quality can automatically adjust processes to maintain consistent 

quality levels. 

7. Data-Driven Insights, Reporting, Compliance: The data collected by industrial 

devices incorporated with IoT technologies can be analyzed to gain valuable 
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insights. This data-driven decision-making can lead to innovations, process 

improvements, and a better understanding of customer needs. It can also 

simplify regulatory compliance by automatically recording and reporting data 

required for compliance purposes. 

The Industrial sector has many existing applicable standards and best practices., As 

an example, this sector utilizes the ISA/IEC 62443 series of standards and conformity 

assessment programs that provide a systematic, practical, and holistic approach to 

address cybersecurity in product development and across the overall product 

lifecycle, starting at its inception. It’s also important to consider how the use cases of 

IoT technologies in the industrial sector are distinct from IoT technologies used in 

other sectors. There are a number of reasons for this listed below.: 

• Use/Scope: IoT in industrial devices are used in settings for manufacturing, 

transportation, energy, and other critical infrastructure. 

• Utility: IoT in industrial devices are used for enhancing productivity, improving 

efficiency, quality and reducing costs in industrial processes. 

• Applications: IoT in industrial devices are used for industrial applications such 

as monitoring and control of machinery, inventory management, and supply 

chain optimization. These operations may be in harsh environments, require 

low latency and may operate in long time scales before replacement. 

• Impact: Cybersecurity breaches in industrial devices with IoT technologies can 

cause significant damage to critical infrastructure, including production 

downtime, supply chain disruptions, and safety risks. 

• Life Support: Some industrial devices with IoT technologies such as medical 

devices and aerospace systems may involve human safety, and their 

cybersecurity vulnerabilities can lead to fatal outcomes. 

• Automation: Industrial devices with IoT technologies are often automated and 

may interact with other machines and systems., 

• Reliability: Industrial devices with IoT technologies must operate reliably and 

continuously in harsh environments. 

• Privacy and Confidentiality: Industrial devices with IoT technologies may 

collect sensitive data, but the privacy concerns may differ based on the 

application. The data being transmitted and processed in Industrial IoT 

environments can be highly sensitive and critical to business operations. This 

includes manufacturing data, process control information, supply chain data, 
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and proprietary intellectual property. Confidentiality in Industrial IoT extends 

beyond personal information to safeguard critical industrial processes and 

trade secrets. 

• Interoperability: Industrial devices with IoT technologies are often part of 

larger systems and must be interoperable with other devices and systems, 

including legacy equipment and other operations technologies. 

• Scalability: Industrial systems with IoT technologies often involve a large 

number of devices and must be scalable to accommodate growth., whereas 

consumer systems with IoT technologies may be smaller in scale 

• Attack Surface: Industrial devices with IoT technologies have a larger attack 

surface due to their connectivity and may be vulnerable to various types of 

cyber threats such as hacking, malware, and ransomware. 

• Criticality: The cybersecurity of industrial devices with IoT technologies is 

critical for the operation of critical infrastructure. 

The advancement of IoT technologies in industrial applications can further amplify the 

efficiencies of the manufacturing process, allowing for production goals and 

outcomes to reach levels of scale that are previously unimaginable and physically 

attainable. And when properly and responsibly governed and applied, these 

technologies can achieve these efficiencies while enhancing workers safety and 

privacy while fostering energy and environmental stewardship. 
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The Current State of IoT

The adoption of IoT is growing in the United States. One industry analyst estimated 

the value of the U.S. IoT market to be $56.3 billion in 2022, growing at 15.6% CAGR and 

projected to reach $270.2 billion by 2033.5 Research published in the 2021 Microsoft 

IoT Signals found that 94% of business decision-makers, IT decision-makers and 

developers at U.S. enterprise organizations (1000+ employees) surveyed are “IoT 

adopters”6

, meaning that they are either learning about IoT, conducting a trial or proof 

of concept, purchasing IoT, or using IoT.7 Of this, 27% have projects in the “use” phase, 

while 78% reported that they are planning to use IoT more within 2 years.8 

However, this growth is below expectations. Adoption of IoT is hindered by a variety of 

industry-specific challenges. For years industry projected 10’s of billions of IoT units in 

use by ca. 2022. And in 2014 the World Economic Forum and McKinsey & Co. projected 

that IoT, and adjacent technologies (analytics, cloud computing, big data and ML/AL) 

will produce $9.6 to $21.6 trillion of value for the global economy by 2022. And Verizon’s 

State of the Market: Internet of Things 2016 report noted, “The installed base of IoT 

endpoints will grow from 9.7 billion in 2014 to more than 25.6 billion in 2019, hitting 30 

billion in 2020.” [1] Verizon was by no means an outlier at that time; while numbers 

varied, most analysts expected this kind of growth over the next few years. 

But in 2021, McKinsey & Co. revised the IoT forecast drastically downward, projecting 

global value of only $5.5 to $12.6 trillion, and not reaching those targets until 2030. 

While the new projection was focused on the top nine categories, it is clear that 

adoption is not as anticipated. The firm clarified that the 2014 projection was off mainly 

due to headwinds related to change management, cost, talent, and cybersecurity. 

They additionally noted factors of slow market adoption of digitalization and cyberresilience, particularly in enterprises. 

And compared to analysts’ ca. 2016 estimates, the IoT is nowhere near on target. 

Verizon said in 2022, “By the end of 2022, it’s estimated that there will be 14.4 billion 

connected IoT devices worldwide, an increase of roughly 18% over last year alone, 

with numbers climbing to 27 billion by 2025.” [2] Comparing the 2022 estimate of 14.4 

BN to the estimate just six years earlier of 30 BN in 2020, clearly something happened. 

5 “United States IoT Market is expected to surpass revenues worth U.S.$ 270.23 billion by 2032: Persistence Market 

Research Report,” Persistence Market Research Press Release, May 24, 2023. Link

6 “IoT Signals - Edition 3|October 2021”, Microsoft, October 2021. Exhibit 3. Link

7 Ibid. Exhibit 2.

8 Ibid. Exhibit 3.
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[1] https://www.verizon.com/about/sites/default/files/state-of-the-internet-of-thingsmarket-report-2016.pdf 

[2] https://www.verizon.com/about/news/5g-iot-together-changing-our-world

Analysts a decade ago saw the incredible potential for IoT growth, but could not 

foresee the barriers to deployment that would significantly slow that growth. Still, the 

difference is between incredible growth, and moderate growth, as IoT adoption is 

definitely rising—just not as quickly as predicted.

Figure 2: Impact of barriers and other factors ("headwinds") on IoT adoption, based 

on industry forecasts. Size of bubble is proportional to the estimate.

IoT is used across a variety of industries for different reasons. For example:

● Manufacturing. The top three reasons for small manufacturers with less than 

500 employees (which make up 98.3% of manufacturing companies in the 

United States), are performance improvement of operational processes, 

achieving production cost efficiencies and filling labor shortages.9 A 2022 

CESMII survey of manufacturers found that the top five smart manufacturing 

goals were better manufacturing capacity utilization (65%), lower production 

9

 “The Manufacturing Institute–BKD Small and Medium-Sized Manufacturers Survey”, The Manufacturing Institute, 

September 2021. Link.
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costs (63%), improved on-time delivery (62%), operational excellence (61%) and 

improved quality/reduced quality risks (60%).10 

● Agriculture. IoT helps lessen the impact of labor shortages and augment 

existing labor resources. A 2018 study estimated that 250,000 farms across the 

United States were using IoT solutions, with most of those in livestock and crop 

management. The study also found that up to half of all U.S. farms were 

interested in purchasing IoT solutions, representing 1.1 million farmers and a 

potential agricultural IoT solution market opportunity of $4 billion dollars.11

● Retail. A 2022 industry survey of 104 large American retailers (with sales of $500 

million and above) by RSR Research reported that the top business challenges 

driving interest in IoT included competitive differentiation (43%), maintaining 

margins (41%), operations cost reduction (40%) and operations speed and 

agility (34%). The top IoT use cases deemed as “very important” centered 

around inventory accuracy and stock management (82%), fraud and loss 

prevention (80%), fulfillment center process automation (65%), supply chain 

process automation (63%), loyalty and personalization (62%) and brand 

protection and anti-counterfeiting (62%).12

● Transportation and logistics. One way IoT technologies help create a resilient 

supply chain is by tracking the real-time locations and quantities of goods and 

inventory across a network of warehouses and distribution centers, enabling 

inventory and logistics planners to draw from the most appropriate locations 

to minimize disruptions.13 Approximately 95 million telematics devices have 

been shipped worldwide as of 2021, and is expected to grow at a CAGR of 10.9% 

reaching nearly 160 million units by 2026.14 It is also estimated that there are 

10 “2022 Smart Manufacturing Market Survey Executive Summary”, CESMII, May 2022, Page 4. Link

11 “Nearly 250,000 U.S. Farmers Already Using IoT Technology, Study Finds”, J. Tomas, May 16, 2018. Enterprise IoT 

Insights. Link

12 “A Deep Dive into Retailers’ Views About Rfid and the Internet of Things”, B, Kilcourse and S. Rowen, Retail Systems 

Research Benchmark Report, April 2022. Link

13 “How telematics and the IoT work together to improve fleet management,” Verizon Connect, June 29, 2021. Link

14 “Outlook on Vehicle Telematics Hardware Global Market to 2026...”. Global Newswire, July 15, 2022, Link
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over 130 million units of embedded car OEM telematics units in operation 

globally as of 2020, and 375 million embedded units by 2026.15

Adoption Barriers

Although IoT offers the potential for significant economic and societal benefits to the 

United States, its overall adoption and deeper integration into the economy and daily 

lives of Americans in a larger way has been slow. There are a myriad of contributing 

reasons, including:

● A lack of national coordination...[This Finding section is incomplete but has 

Board members tasked to fill it out] 

● A need for suppliers to adopt new smart-connected-product business models 

with new services models and revenue streams.

● Various existing policies and regulations at local, state and federal levels.

● An unsustainable inequitable share of access, opportunities, benefits and 

outcomes from IoT.

● Lack of interoperability hinder integration and communication with other IoT 

devices and existing systems and processes

● Limited and outdated infrastructure, such as connectivity and legacy systems, 

to support, operate and scale IoT systems. 

● A variety of network connectivity challenges particularly in remote 

communities.

● Concerns about IoT cybersecurity vulnerabilities that may lead to an intrusion 

of the user’s network, theft of sensitive and proprietary data, unauthorized 

control of systems, and loss of network access.

● Concerns about privacy involving the unauthorized collection and use of 

information collected from IoT devices and systems. This information may be 

used in an adverse and discriminatory manner, limit choice, and create 

negative outcomes for the user.

15 “Number of embedded auto telematics units n operation worldwide in 2019 and 2020...”, Martin Placek, Statista, 

March 23, 2023. Link
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● A slow adoption of enterprise digital transformation elements that enable and 

accelerate IoT benefits. 

● A shortage of workers with expertise, digital and data science skills to develop, 

integrate and operate IoT and IoT enabled systems. 

● And a variety of sector-specific challenges

Market Consolidation

There is no “one size fits all” IoT technology. The market is an organically-developing 

but fragmented ecosystem of sensors, chips and processors, modules, devices and 

software platforms16. For example, there were 613 IoT software platforms in the 

market in 2021, down from 620 in 2019, but up from 450 in 2017.17 The fragmented 

nature of the market has created confusion for IoT buyers who have struggled with 

understanding, selecting and integrating hardware and software from a vast array of 

technology providers to meet their specific requirements. 

Today, this large and fragmented IoT market is consolidating in order to create value 

for buyers, scale and profitability at the current market levels. Some recent mergers 

in the news include:

● IoT module maker Telit acquires Thales cellular IoT products company (2022)18

● Semiconductor manufacturer Semtech acquires IoT technology provider Sierra 

Wireless19 

● Kore acquires Twilio’s IoT business (2023)20

● Renesas acquires IoT chip and module provider Sequans Communications 

(2023)21

16 [1] “IoT platform” is an application or service that provides IoT product suppliers with tools and capabilities that 

they would otherwise need to develop in-house. Platforms ease development and assist with the product lifecycle 

after the product is shipped by providing such features as automated software updates or data analytics. 

17 “IoT platform companies landscape 2021/2022: Market consolidation has started,” P. Wegner, IoT Analytics, 

November 23, 2021. Link 18 “Telit acquires Thales’ cellular IoT products to establish Telit Cinterion,” R. Daws, IoT News, August 1, 2022. Link

19 “Semtech Corporation to acquire Sierra Wireless,” Semtech press release, August 2, 2022. Link

20 “Twilio Sells Its IoT Business Unit to Kore,” J. Stephen, CX Today, April 3, 2023. Link

21 “Renesas to broaden IoT offering through Sequans acquisition,” L. Redins, Edge Industry Review, September 5, 2023. 

Link
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● Unabiz acquires IoT connectivity provider Sigfox (2022)22

Other market players have not achieved the level of success envisioned and have 

exited the IoT market or cut staff. Notable announcements include: 

● Google exiting the IoT services business (2022)23

● Ericsson sells IoT business (2022)24

● IBM shuts down Watson IoT (2022)25

● SAP retires IoT platform (2022)26

● Cisco exits smart city market (2020)27

● Hologram lays off 40% of workforce (2022)28

[This section below is from Tom’s findings document. Although Tom calls it a finding, 

I don’t consider it a finding, but commentary that belongs here instead. I just cut and 

pasted his content verbatim. There is some good content here that supports and 

complements the above content on consolidation and industry state. Some duplicate 

what is here, but there are some new information as well that we could use. There is 

too much content and some can be cut out].

Commercial IoT platforms are consolidating while partnerships among 

companies using IoT platforms for end-to-end solutions are growing. New models 

of platform-based public private partnerships and business ecosystems emerge. 

The IoT platforms landscape is consolidating, as reported by IoT Analytics29, with a 

growing trend in forming end-to-end solutions partnerships using these platforms. 

This approach accelerates IoT technology adoption by offering incentives to partners 

who utilize these platforms, which benefits their businesses, creates new workforces, 

and fuels economic growth.

22 “IoT firm Sigfox acquired by UnaBiz,” A. Wooden, Telecoms, April 22, 2022. Link.

23 “Google to shut down its IoT Core Services from Aug 2023; users seek options,” Business Standard, August 18, 2022. 

Link

24 “Ericsson quits IoT - agrees sale of loss-making IoT accelerator business to Aeris,” J. Blackman, RCR Wireless 

Business, December 7, 2022. Link

25 “IBM to fire Watson IoT Platform from its cloud,” L. Clark, The Register, November 15, 2022. Link

26 “SAP IoT Retirement and SAP Asset Performance Management,” S. Lee, SAP, October 5, 2022. Link

27 “Cisco Systems pulls back from smart city push,” A. Tilley, Wall Street Journal, December 28, 2020. Link

28 “Hologram lays off 40% Workforce – 80+ Employees,” Layoffs Tracker, June 9, 2022. Link

29 https://iot-analytics.com/iot-platform-companies-landscape/ 
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IoT Platforms are software systems used to develop or manage solutions. IoT 

platforms are classified into five types: application enablement and management, 

device management, data management, telco connectivity and management, and 

IoT-based Infrastructure-as-a-Service (IaaS). Platforms have revolutionized the way we 

conduct business, have disrupted traditional business models, and have become an 

important force in the global economy. 

Since 2019, IoT Platform companies are transitioning into solutions. Some 

companies folded, some pivoted their business models, and some transitioned from 

IoT software tools to IoT solutions. The total number of IoT platforms based in AsiaPacific (APAC), especially China, grew rapidly from 2019 to 2021, while the number of

platforms in all other major regions decreased. IoT solutions partnerships almost 

always include the top 10 platform companies.

The market for IoT Platforms continues to consolidate with Hyperscalers 

dominating. In 2023, the top 10 companies controlled 65% of the market, compared 

to 58% in 2019 and 44% in 2016. Leading Hyperscalers (Microsoft, AWS, Alibaba) 

continued to outgrow the market with growth rates of 50%+ per year since their 

platforms enable business ecosystems and scalable revenue streams. Platform-based 

partnerships successful collaborations for various markets.

Technology Maturity

The technology enabling IoT continues to evolve. IoT is an evolving set of disparate 

technologies at various levels of maturity. While some are mainstream and mature, 

others are emerging and immature. Technologies such as cloud computing, IoT 

platforms, containers, supervised machine learning, IoT streaming analytics, cellular 

IoT and Low Power Wide Area Networks (LPWAN) have reached a certain level of 
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maturity.30 Others are “coming up”, including edge data and app platforms, 

serverless/Function-as-a-Service, cloud-connected sensors, edge AI chips, and low 

code/no code development platforms and satellite IoT connectivity.31 Still others like 

data ecosystems, automated machine learning, wireless battery-free sensors, 

neurosynaptic chips, QRNG chips, biodegradable sensors, 6G and quantum 

computing are only just hitting the market or are still in research labs. still “years out” 

and require continued research investments.32

Figure out what to do with this content – delete or move somewhere.

Emerging trends for digital platforms require a change in partnership models. 

Moving forward, interconnected ecosystems are expected to drive integration 

between IoT and AI that enables circular economies for sustainability, connected 

manufacturing, and challenges such as value creation, regulation, and 

misinformation. Partnerships that serve specific needs like the ones shown here will 

no longer be scalable. New Public Private Partnerships (PPPs) that align business 

incentives and industry standards for broader hyper-connected use cases will emerge.

Platform-based business ecosystems driven by Hyperscalers can create enormous 

value. The key challenge is how to drive scalable collaboration among ecosystem 

partners in ways that help Small Medium Enterprises (SMBs) grow, instead of their 

value-add being exploited. 

The Future of IoT

From a device deployment perspective, as the physical environment is equipped with 

more and more sensors, the way those sensors and devices are used will evolve. Many 

of the devices deployed today largely operate in isolation or “islands”. However, as IoT 

matures and interoperable technology platforms emerge, the “islands” of devices 

integrate to form systems of connected devices and larger ecosystems of benefits for 

a plethora of users. 

From an ecosystem perspective, systems of connected devices integrate with other 

systems to form broader and bigger “systems of IoT systems”. In a smart factory 

example, individual IoT applications in a factory integrate to create a smart factory. 

These smart factories connect with others to share data and create a network of smart 

30 “55+ emerging IoT technologies you should have on your radar (2022 update),” S. Sinha, IoT Analytics, April 6, 2022. 

Link

31 ibid.

32 ibid.
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factories. These smart and connected factories form a virtual factory network that 

offers “production as a service”. Customers find available factory capacity online and 

route files and orders to open factories for production. The data from these smart 

factory networks integrate with IoT applications across industries, such as freight and 

logistics providers, to coordinate the delivery of raw materials to factories and finished 

products to distributors and retailers. Finally, the integration of data and operations 

within and across industries leads to the formation of the fully autonomous factory 

and supply chain.

From scaling technology from today to tomorrow, we can envision new innovative 

business models which require partnerships and incentives for growth for all 

participating stakeholders. Value generated can provide future opportunities through 

parallel ecosystems or rather the ecosystem at the largest scale to provide better 

economic outcomes for society. This transformation has already seen things become 

‘smart’ and as the data of things is becoming more utilized through the systematic 

integration of algorithms and analytics. The future is more predicated on the 

advancement of emerging technologies, the utility and outcomes of those future 

integrations, and at large a hyperconnected economy with full autonomy by 

machines. IoT enables new innovative business models which require partnerships 

and platform-based business and technology ecosystems that incentivize growth for 

all participating stakeholders across diverse disciplines.

Figure 2: The future of IoT Solutions and Services

Finding: IoT enables new innovative business models which require partnerships 

and platform-based business and technology ecosystems that incentivize growth 

for all participating stakeholders across diverse disciplines.
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Platform-based business ecosystems are proven to grow rapidly and create enormous 

value. IoT provides opportunities to evolve partner ecosystems that promote business 

collaboration. 

IoT solutions require orchestrated business ecosystems with clear roles. Private 

Public Partnerships (PPPs) including broadline suppliers, innovative startups, and 

application domain experts can be a catalyst to growth. Orchestration requires rethinking the roles of ecosystem participants as proposed by Deloitte33, which must be 

clearly defined to support a collective mix can bridge the gaps between legacy 

infrastructure and IoT markets to accelerate IoT adoption. 

Platform Ecosystem Orchestration Transforms Linear Supply Chains to Value 

Chains. Boston Consulting Group has published an analysis on how IoT offers a 

transformative opportunity to shift from traditional linear supply chains to multiindustry value chains34. By aggregating data from products or business processes, 

industries can create IoT platform35 businesses and ecosystems that serve diverse user 

33 https://www2.deloitte.com/xe/en/insights/focus/industry-4-0/partner-ecosystem-industry-4-0.html 34 https://www.wallstreetmojo.com/supply-chain-vs-value-chain/ 35 https://www.bcg.com/publications/2020/value-in-iot-platform-based-business-models 
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bases. These platforms invite contributions from other companies, fostering 

collaboration and the exchange of data, products, and services, ultimately breaking 

down industry silos and creating rapid growth driven by network effects36. 

 

Digital platform network effects are key to accelerating growth of business 

ecosystems. A platform-based digital marketplace can be established by identifying 

numerous high-value use cases within a single industry or across industries that 

benefit from network effects. Such marketplaces connect buyers and sellers. As more 

customers and a wider range of equipment join, the value of the platform grows with 

more stakeholders and applications. Once a strong market presence of suppliers and 

buyers is established, third parties introduce digital services. 

Tech innovation hubs37 are key for orchestrating ecosystems that accelerate 

adoption. They provide the ability to orchestrate the right mix of partners for Proof of 

Concept (PoC) pilot projects that can show the economic value before investing to 

deploy at scale. Broadline suppliers bring platform orchestration capabilities, startups 

push the boundaries of IoT with innovation, and domain experts provide real-world 

relevance optimizing for practical use. Innovative startups and SMB’s, especially the 

ones that are domain experts in specific market applications and application 

36 https://www.wallstreetprep.com/knowledge/network-effects/ 37 https://www.eda.gov/funding/programs/regional-technology-and-innovation-hubs 
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environments, must be incentivized to use Hyperscalers’ platforms in was that help 

them attract skilled personnel, innovate, and grow open business ecosystems

Tech hubs enable innovative ecosystems to fuel economic, financial, and social 

benefits. Public-private partnerships (PPPs) led by tech hubs effectively manage risks 

and deliver scalable solutions that promote economic growth. Innovation hubs bring 

together diverse stakeholders like R&D institutions, venture capital, incubators, 

startups, and businesses, fostering innovation, attracting talent, and creating 

economic opportunities. Tech hubs can lead innovation ecosystem orchestration, 

emphasizing priorities such as talent attraction, capital investment, strengths 

identification, and comprehensive support. 

Finding: Orchestrated Business Ecosystems enabled by collaborative platforms 

with appropriate mix of large companies, innovative startups, SMBs and end 

market domain experts can accelerate IoT adoption and fuel economic growth.

Successful innovation ecosystem development relies on network effects for 

relationship-building, addressing business gaps, and meeting the needs of small and 

large businesses through collaboration. Orchestrated innovation ecosystems must be 

driven by business use cases that provide business incentives for all participating 

stakeholders. The U.S. federal government must promote initiatives to operationalize 

such ecosystems with few Hyperscalers to use their platforms to accelerate growth of 

the many SMBs, instead of using their value-add to increase monopoly. Below are 

business use case examples that can be accelerated with orchestrated PPPs 

consisting of large companies, innovative startups, and domain experts. 

Smart Connected Cities: IoT systems collecting data on traffic, pollution, etc. to 

improve city lifestyle.

Platform-based business ecosystem partnerships 

may include broadline chip suppliers (e.g., 

Qualcomm), device makers (e.g., Cisco), 

Hyperscalers (e.g., AWS), PLM vendors (e.g., 

Siemens), innovative startups (e.g., UrbanData 

Analytics), and city planners. 

For collaboration, broadline suppliers lead the with foundation IoT platforms, cloud 

vendors offer data storage and processing, PLM vendors assist in managing city 

assets, startups and domain experts add value by providing innovative applications 

for traffic management, pollution reduction, or urban planning and city governments 

facilitate data access and policy implementation. The economic value proposition for 

stakeholders includes enhanced city services, reduced traffic congestion, improved 
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air quality, and a higher quality of life and improved city lifestyle and future economic 

growth. 

Smart Connected Manufacturing: Factories using sensor data to improve 

efficiency, automation, and quality.

Platform-based business ecosystem partnerships 

may include chip suppliers (e.g., NVIDIA), device 

makers (e.g., Siemens), cloud vendors (e.g., Azure), 

PLM vendors (e.g., PTC), OEMs (e.g., GE), innovative 

startups (e.g., QualitySense) and manufacturing 

experts. 

For collaboration, large companies like Shneider, ABB, Siemens, PTC and GE offer 

industrial IoT platforms, while innovative startups like QualitySense provide 

specialized solutions for quality control and process optimization. Chip suppliers like 

Nvidia contribute AI and IoT hardware, while domain experts in manufacturing 

processes collaborate on real-time data analytics and automation. The economic 

value proposition for all stakeholders, centers on increased efficiency, reduced 

downtime, improved product quality, and cost savings, benefiting both large and 

small enterprises that jointly offer unique solutions.

Smart Connected Buildings: Sensors monitor activity and manage power or find 

doctors in hospitals.

Platform-based business ecosystem partnerships may include device makers (e.g., 

Honeywell, Johnson Controls), Hyperscalers (e.g., Google Cloud), innovative startups 

(e.g. EcoSensors) that offer energy-efficient sensor technology and domain experts in 

building management and energy efficiency. Chip suppliers like Intel, ST and NXP can 

power smart buildings apps. 

For collaboration device makers provide 

sensors and automation systems, cloud 

vendors handle data analytics and storage, and 

building experts. Innovative startups ensure 

that the sensor data collected is effectively 

utilized to optimize building management

such as power consumption and occupancy 

tracking. The economic value proposition for participating stakeholders includes 

reduced energy consumption, cost savings, and optimized building management, 

with all stakeholders benefiting from better efficiency and enhanced building 

functionality.
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Smart Connected Transportation: Connected EVs becoming Autonomous and 

integrated with city infrastructure.

Platform-based business ecosystem partnerships may include Automotive OEMs 

(e.g., Tesla, VW), infrastructure providers (e.g., Siemens), Chip suppliers (e.g., AMD, 

Infineon), innovative startups like AutonomyTech focusing on automated vehicle

software development and city municipalities. 

For collaboration, EV manufacturers develop 

connected vehicles, infrastructure providers 

create charging stations and autonomous 

infrastructure, and city governments facilitate 

integration with urban planning. Large EV 

manufacturers and infrastructure providers pave 

the way with platforms, while startups focus on 

software development and integration, enabling a transition to automated vehicles 

applications integrated with city infrastructure. The economic value proposition for 

stakeholders includes reduced traffic accidents, enhanced mobility, and efficient 

transportation systems, benefiting all stakeholders through safer and more efficient 

transportation options. 

Smart Connected Energy: Utility companies use Smart meter analytics to balance 

energy supply and demand.

Platform-based business ecosystem 

partnerships may include leading utility 

companies (e.g., E.ON, PG&E), OEMs (e.g., 

Schneider), Smart Connected meter suppliers 

(e.g., Landis + Gyr), data analytics firms (e.g., SAS) 

and chip suppliers (e.g., Renesas), and startups 

(e.g., Bidgely).

For collaboration, utility companies license and deploy software platforms from 

innovating startups offering analytics into energy consumption and managing 

energy demand and supply of the overall grid. Meter suppliers provide hardware, data 

analytics firms offer insights, and energy experts optimize the grid for supply and 

demand balancing of the Connected Energy ecosystem. The economic value 

proposition for stakeholders revolves around reduced energy waste, lower costs, and 

improved grid reliability, benefiting utility companies, analytics providers, and 

consumers.

Smart Connected Healthcare: Wearables collecting health data and provide 

analytics to prevent emergencies.
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Platform-based business ecosystem partnerships may include large consumer tech 

companies (e.g., Apple), data analytics providers (e.g., IBM Watson Health), innovative 

startups on medical data analysis (e.g., HealthTech Insights), healthcare institutions, 

and medical expert networks. 

For collaboration, large companies deliver 

wearables and data analytics tools that capture 

health data, while startups contribute 

specialized medical data analysis, healthcare 

institutions utilize insights, and medical experts 

provide guidance to help prevent emergencies 

through early detection and proactive health 

management. The economic value proposition for stakeholders includes improved 

health outcomes, reduced healthcare costs, and early intervention where all parties 

benefit from proactive healthcare management. 

Smart Connected Agriculture: Sensors and drones help increase crop yield and 

reduce spoilage in storage.

Platform-based business ecosystem partnerships may include agriculture leaders 

(e.g., John Deere) drone manufacturers (e.g., DJI), Hyperscalers (e.g. Azure, AWS) 

innovative startups of drone sensors data analytics (e.g., PrecisionHawk) or spoilage 

sensors and analytics (e.g., Centaur Analytics) and agronomist experts.

For collaboration agriculture technology firms 

supply sensors and solutions, drone 

manufacturers offer aerial monitoring 

technology, startups provide drone-based 

monitoring solutions to increase crop yield 

and sensor-based solutions to reduce spoilage 

in storage, while agronomists leverage data for 

crop management and optimization. The economic value proposition encompasses 

increased crop yields, reduced spoilage, and sustainable farming practices, benefiting 

all stakeholders with better agricultural capacity and reduced waste.

Smart Connected Supply Chain: Tracking sensors on boxes & containers reduce 

costs and strengthen resilience.

Platform-based business ecosystem partnerships may include logistics giants (e.g., 

UPS), sensor technology providers (e.g., Bosch, TI, ST Microelectronics), innovative 

startups offering real-time visibility (e.g., Resilinc), and supply chain experts. 

Ecosystem partnerships vary by vertical market as shown below.
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For collaboration, logistics companies deploy 

tracking sensors, sensor technology providers 

supply IoT hardware which connects to 

company IT infrastructure, and supply chain 

experts optimize logistics based on real-time 

data and technology startups offer real-time 

visibility into supply chain events and helps 

organizations proactively identify and mitigate risks. The economic value proposition 

includes cost reduction, improved supply chain resilience, and enhanced efficiency, 

benefiting all participants through reduced operational costs and improved supply 

chain reliability. 

Platform-based business ecosystems driven by orchestrated PPPs are crucial for 

IoT adoption and growth due to its complexity and critical need for integration and 

interoperability of many components. Collaboration among stakeholders with a joint 

business objective involves clear communication, trust-building, alignment of 

incentives, network affects and the establishment of governance to ensure that all 

parties work together toward a common goal.

Finding: IoT can have a positive impact on our GDP by leveraging platform giants 

to lead the development of orchestrated digital business ecosystems linking 

industries, environments, and digital marketplaces into a hyper-connected 

planet. 

In an age of unprecedented technological advancement, the Internet of Things (IoT) 

emerges as a transformative force with the potential to reshape our GDP. IoT can 

positively impact our economy by harnessing the prowess of digital platform giants 

like Apple, Microsoft, Google, and Amazon. Their collective value represents a major 

portion of the U.S. GDP. Their collective might and platform experience can be 

leveraged to lead the evolution of a hyper-connected planet connecting industries, 

environments, and digital marketplaces. 
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Void in orchestrated platform-based business ecosystems. While the platform 

giants have excelled in various domains, there remains a noticeable void on multistakeholder collaboration platform across industry ecosystems. One of the main 

strategies for achieving hyper-connected growth is to create orchestrated platformbased business ecosystems linking IoT value chains. This approach recognizes that 

the digital landscape is evolving rapidly, and that legacy business models are being 

reshaped by the advent of IoT technologies. With appropriate orchestration and 

incentives, the few trillion-dollar giants can multiply the growth of the many SMBs.

The journey from partnerships to knowledge networks, to digital ecosystems.

Digital ecosystems are not limited to the exchange of goods and services. They 

encompass a broader spectrum, starting with partnerships where entities collaborate 

to achieve shared goals. Over time, partnerships evolve into knowledge networks, 

emphasizing the importance of sharing expertise and insights among stakeholders. 

Knowledge networks mature into collaborative platform-based business ecosystems 

leveraging the collective IQ and digital threads across value chains to surge in new 

XaaS revenue streams with amplified network effects.

Strategy for giants to empower SMBs to scale with massive collaboration.

Platform-based business ecosystems that span across IoT ecosystems amplify 

network effects exponentially, setting the stage for a dynamic and collaborative 

business landscape. To unlock this potential, the platform giants should spearhead 

orchestrated platform-based business ecosystems in ways that strengthen national 

security and fuel economic growth. Rather than exploiting SMB value-add in their 

own ecosystem to increase their monopoly, they should be incentivized to amplify 

and multiply the value-add of SMBs to create the next generation of trillion-dollar 

giants. 

Harnessing data for national security and economic Growth. By motivating the 

platform giants to orchestrate multi-stakeholder digital business ecosystems and 

hyper-connected marketplaces driven by trusted digital threads, the treasure trove of 

data generated by digital twins and AI applications will be unlocked. This data will fuel 

a plethora of digital services, enhancing national security and propel our economy 

into the future of a hyper-connected digital planet. Large and small businesses will be 

able to access a vast marketplace where they can not only offer their products and 

services but also tap into a wealth of data and insights. 

Leveraging circular value chain ecosystems for sustainability. Platform-based 

business ecosystems in circular value chains play a pivotal role in driving sustainability 

and accelerating the convergence of physical and digital worlds with digital twins. 

Digital twins being replicas of physical systems integrated into circular ecosystems, 

will contribute to collective ecosystem IQ amplified by network effects evolving new 
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layers of digital twins. The convergence of physical and digital words, fueled by digital 

twins within circular business ecosystems, fosters efficiency, innovation, and 

environmentally responsible practices that will take economies to the next level.

The convergence of IoT and platform giants leading the development of orchestrated 

business ecosystems represents an unparalleled opportunity to grow our GDP. 

Through collaboration, amplification of SMB value, and the adept leveraging of hyperconnected digital threads, the U.S can usher in an era of prosperity and innovation. It 

is incumbent upon us to leverage the core strengths of the giants and harness the full 

potential of IoT and lead the charge toward a future of orchestrated digital business 

ecosystems that unite digital marketplaces, industries, and environments and a 

hyper-connected planet that holds untold promise for us all. By embracing this 

strategic transformation, we secure our place at the forefront of the digital revolution, 

ensuring a brighter future for generations to come.
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Findings of the IoT Advisory Board

The major findings that informed the board on the development of the 

recommendations are listed in this section. These findings are grouped in general 

findings (affecting everyone) and industry-specific findings.

General findings

1. Industry adoption is slower than expected and is hindered by a variety of 

challenges. 

2. A lack of coordination at the national level is hindering IoT adoption and 

operation across the economy and industry sectors.

3. The adoption and operation of innovative IoT applications are hindered by 

various existing policies and regulations at local, state and federal levels.

4. Equity in access, opportunities, benefits and outcomes is necessary for the 

sustainable integration of IoT into all aspects of the national economy and civil 

society.

5. Small businesses can reap significant benefits from IoT, but significant barriers 

hinder adoption.

6. Small companies and startups are instrumental in developing many innovative 

and disruptive technology solutions and services but face a variety of barriers 

in getting adoption.
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7. IoT enables new innovative business models which requires new business and 

technology platforms and ecosystems to support and scale it. 

8. Interoperability is a key challenge for IoT across multiple industries

9. A variety of connectivity challenges is hindering IoT adoption, operation and 

scaling.

10. A lack of trust in IoT is a major barrier to widescale adoption.

11. Artificial Intelligence (AI) is critical to unlocking and accelerating the value of 

IoT.

12. There is an insufficient number of people in the current workforce with the 

technical, digital and analytic skills required to develop, integrate and deploy, 

operate and maintain IoT devices and IoT-enabled systems and applications. 

Industry findings

1. Precision Agriculture: IoT brings significant value to agriculture, but adoption is 

slow.

2. Smart cities and infrastructure: The development of smart cities in the United 

States is limited, uneven and slow to develop.

3. Transit and traffic: IoT is transforming transit systems and traffic management 

with real-time data analytics, intelligent traffic management, and predictive 

analytics to enhance efficiency, reduce congestion, increase safety, and 

improve overall transportation experiences.

4. Healthcare: IoT is transforming healthcare, and is poised to revolutionize it but 

significant challenges need to be addressed.

5. Environmental Sustainability: IoT supports environmental sustainability 

through real-time monitoring, optimizing resource usage, and facilitating datadriven decision-making across infrastructure and multiple sectors of the 

economy.
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General Findings – Specific Considerations

Finding: Industry adoption is slower than expected and hindered by a 

variety of challenges. 

Supports Recommendation(s) x.x, x.x

In 2014 the World Economic Forum and McKinsey & Co. projected that IoT, and 

adjacent technologies (analytics, cloud computing, big data and ML/AL) will produce 

$9.6 to $21.6 trillion of value for the global economy by 202276. 

In 2021, McKinsey & Co. clarified in a new report77 that the above projection was off 

mainly due to The IoT has faced headwinds related to change management, cost, 

talent, and cybersecurity, and slow market adoption of digitalization and cyberresilience particularly in enterprises. 

 

76 www.weforum.org/press/2014/01/increased-cyber-security-can-save-global-economy-trillions/ 77 www.mckinsey.com/capabilities/mckinsey-digital/our-insights/iot-value-set-to-accelerate-through-2030-whereand-how-to-capture-it 
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The 2021 report revised the IoT forecast to $5.5 to $12.6 trillion by 2030 concentrated in 

certain settings as shown above. For each setting, it provided a min-max range for 

projections factoring adoption rates, impact, and scale. Each setting was analyzed 

for tailwinds and headwinds, opportunities and risks and the settings were ranked 

based on size and growth rates as shown in the chart above. The convergence of 

physical and digital worlds was cited as a fundamental trend underlying the digital 

transformation of businesses that can fuel the global economy.

Despite the significant value of IoT and projections about its potential to accelerate 

economic value the rate of adoption and growth is still slow. However, some key 

barriers to adoption across value chains are economic, such as upgrading legacy 

infrastructure, handling enterprise silos, optimizing fragmented supply chains 

delivering solutions requiring broad partnerships. To compete, the U.S. must leverage 

existing strengths and experience of the few trillion-dollar companies and replicate 

across the many smaller companies and SMBs. 

The adoption of IoT technologies has been growing in the United States, but that 

growth has been gradual and slower than expected. As a result, several major 

technology companies have pivoted away from IoT. Despite its potential, there are 

several challenges and barriers that have contributed to the slow pace of adoption 

across the economy and society. 

• Complexity and Integration. IoT is a set of disparate technologies offered by a 

fragmented ecosystem of hardware suppliers, software platforms and 

connectivity service providers. It is not a “one size fits all” and components must 

be assembled together to create a solution that meets the specific 

requirements. In addition, IoT implementations often require integration with 

existing systems and infrastructure. Integrating IoT devices and platforms with 

legacy systems is a significant barrier, costly, and requires technical skills that is 

in short supply, especially for industries with established processes. 

• Cybersecurity Concerns. IoT introduces a vast number of potential attack 

surfaces, leading to very real concerns that hinder adoption. Many industries, 

particularly those dealing with sensitive data or critical infrastructure, are 

cautious about the potential vulnerabilities associated with IoT devices. 

Significant progress has been made in IoT security but many manufacturers 

have not yet moved to secure by design/ secure by default cultures. Policies 

must focus on ensuring adoption of best practices and ensuring regular 

updates to IoT devices. 

• Cyberattacks may disrupt the operation of IoT devices and services, or lead to a 

breach of back office and enterprise systems that the IoT devices connect to.
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• Interoperability. The inability for devices to communicate with each other or 

to the broader enterprise, legacy systems and operations technology systems, 

is a major barrier. In some cases, the lack of interoperability is caused by a lack 

of standards and protocols. In other cases, there are multiple competing 

standards as each solution provider creates “walled gardens” or “walled 

ecosystems”. One major challenge is the integration of IoT devices with legacy 

and operations technology systems, which are commonly found in many 

industrial and enterprise environments.

• Data Privacy and Compliance. Concerns related to data privacy and regulatory 

compliance are significant barriers to IoT adoption. Industries must navigate 

complex legal frameworks and ensure that IoT implementations comply with 

data protection regulations, which can slow down the adoption process. While 

privacy concerns cut across multiple markets and industries, certain markets 

are more sensitive to privacy issues, including smart cities, retail, insurance and 

healthcare.

• High Implementation Costs. The upfront costs associated with implementing 

IoT solutions, including the purchase of devices, infrastructure, and integration 

expenses, can be a deterrent for many potential adopters, especially for those 

operating on tight budgets. It is estimated that the cost of the IoT solution 

represents 30% of the total cost, while implementation and deployment 

accounts for the other 70%.

• Lack of Skilled Workforce. Implementing and managing IoT technologies 

require a skilled workforce with expertise in wide variety of areas such as 

cybersecurity, data analytics, application development, cloud operations, and 

system integration. The shortage of professionals with these skills hinder 

adoption, particularly in industries that have not traditionally require digital 

talent. In addition, the ongoing labor shortage contributes to the struggle to 

attract and retain such talent.

• Uncertain ROI and Business Value. Some industries are more hesitant to 

adopt IoT technologies due to uncertainty about the return on investment 

(ROI) and the overall business value. This is particular true for industries, such 

as mining, construction and agriculture, that have not traditionally 

incorporated digital technologies into its operations. There is a lack of clear use 

cases and success stories demonstrating tangible benefits are essential for 

convincing businesses to invest in IoT. 

• Resistance to Change. Resistance to change within organizations is a 

common challenge. Many potential adopters have limited awareness and 
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education of IoT, and what it can do. Employees and management may be 

accustomed to traditional processes and may resist adopting new 

technologies. Complexity, industry regulations and structure, and organization 

culture are additional barriers hindering the adoption of IoT.

• Reliability and Stability Concerns. IoT is still considered a new or emerging 

technology for many industries, particularly those in sectors like healthcare, 

manufacturing, energy and smart cities. In this sectors, reliability, stability and 

longevity are important characteristics. The failure of a smart healthcare device 

may result in the death of the patient. Failure of an intelligent traffic signal may 

lead directly to accidents and injuries. Failure of such systems may result in the 

adopters incurring financial liability. In sectors like cities, maintenance and 

operations are a top requirement, and IoT devices are expected to last decades. 

In these sectors, adopters often forgo the “latest and greatest” technologies for 

older generation “tried and true” systems.

Finding: A lack of coordination at the national level is hindering IoT 

adoption and operation across the economy and industry sectors.

[dan, pete to supply content]

Finding: The adoption and operation of innovative IoT applications are 

hindered by various existing policies and regulations at local, state and 

federal levels.

Supports Recommendation(s) x.x, x.x

Technology advancements create intended and unintended outcomes that are both 

positive and negative. Government policies and regulations help inform, facilitate and 

reduce the impact of unintended consequences. While the outcomes of regulations 

and policies on mature technologies have been studied and understood, new and 

emerging technologies often outpace the effectiveness of policies and result in 

unintended consequences. 

While IoT offers the potential for disruptive transformation and value, there are 

instances where policies and regulations at various levels of government hamper the 

benefits it provides. Policies and regulations are generally well-intentioned and 

crafted to protect users and the community from harm, or to comply with standards 

and norms. Conflicts arise because the development and use of technology is moving 

and changing fast, and used in ways that have never been used or studied before. 

These well intended policies may conflict with one another, resulting in barriers to 

adoption, use, compliance and commerce of IoT. Government policies and regulations 
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play a critical role in advancing or stifling the use, the beneficial outcomes and the 

scaling and evolution of IoT.

Examples of policies affecting the use of IoT include 

• Facial recognition algorithms running on a city’s network of video cameras 

helps to deter and solve crimes but may lead to privacy violations when it is 

used outside of its intended purpose or provide inaccurate results. Many cities 

have enacted laws restricting the use of video cameras and facial in smart city 

applications. 

• Autonomous drones can perform a variety of labor-saving tasks on large farms, 

including monitoring plant health and crop spraying. However, FAA regulations 

require one operator per drone, and it must be operated within line of sight. 

This limits the utility and value that can be obtained from the use of drones in 

agriculture.

• Telematics devices generate a lot of information about a car and driver’s 

behaviors. This information can be used by automobile insurance companies 

to create personalized insurance products and set premiums. Insurance is 

regulated at a state level, and each state determines what information can be 

used. For example, California only allows insurance companies to use mileage 

data.

Finding: Equity in access, opportunities, benefits and outcomes is 

necessary for the sustainable integration of IoT into all aspects of the 

national economy and civil society. 

Supports Recommendation(s) x.x, x.x

Although IoT offers the potential for significant benefit to people, communities, 

businesses and organizations across the United States, those benefits are not equally 

distributed or shared. Conversely, IoT may create adverse outcomes, with some 

communities disproportionately receiving more harm than others. Equity in access, 

opportunities, benefits and outcomes is necessary for the sustainable integration of 

IoT into all aspects of the national economy and civil society. Policymakers, regulators, 

and financiers must understand and consider equity when planning initiatives to 

accelerate and increase the adoption of IoT into the economy and society. Similarly, 

Recommendations: 2.1.1, 3.1.7, 

6.1
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builders, developers and operators of IoT products and services should take equity in 

consideration to create offerings that are relevant, effective, and sustainable. 

Equitable access to connectivity. Connectivity is necessary for the operation of IoT. 

However, many communities today do not have access to connectivity, or to service 

at the levels necessary to support their needs. This lack of access may be due to a lack 

of infrastructure, lack of access to affordable service, or insufficient infrastructure. For 

example, rural and remote communities lack broadband infrastructure, while lower 

socioeconomic communities in urban areas suffer from a lack of affordable service. 

Other communities may have old infrastructure that must be upgraded to support 

advanced IoT applications and services. Equity in connectivity is necessary to enable 

equity of benefits from IoT.

Equitable benefits for rural communities and economies. Rural communities face 

challenges that their urban counterparts do not. For example, many rural areas are 

“medical deserts”, a term used to describe locations with inadequate access to one or 

more kinds of medical services. Approximately thirty million Americans, many in rural 

communities, live at least a sixty-minute drive from a hospital with trauma care 

services.1 In these communities, IoT-enabled telehealth services are of great benefit, 

especially for those with chronic health conditions requiring frequent doctor visits. 

However, rural regions lack not only the connectivity infrastructure, but the workforce 

and resources to support IoT operations. From maintaining connectivity to 

developing, integrating and servicing IoT applications and equipment, a lack of local 

expertise and trained resources is hindering the ability of rural economies to sustain 

and extend its benefits from IoT. 

Equitable opportunities for small cities and communities. Small cities and 

communities lack the capital, resources and capabilities that their larger city 

counterparts enjoy. IoT and other innovations offer the potential of helping these 

smaller cities and communities “do more with less” and to do it more effectively to 

serve the needs of their constituents. However, these smaller cities and communities 

are often less aware of IoT and other innovations, lack the budget and access to 

funding sources, and in-house expertise and capabilities to plan and deploy these 

technologies. Furthermore, the lack of innovation offerings, enablement programs, 

and funding sources is hindering these smaller communities from accessing the 

same opportunities and benefits that their larger counterparts receive.

Equitable outcomes from data. IoT devices collect vast amounts of private and nonprivate data to make decisions, drive actions and create outcomes. However, the use 

of this data may lead to negative outcomes intentionally or unintentionally. For 

example, the use of facial recognition on people of color has been found to have a 

higher probability of error and lead to inaccurate results. Because of this, people of 
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color have been negatively impacted at higher rates than other demographic groups. 

Similarly, vehicle telematics data can be used by insurance companies to determine 

risk and set personalized premiums. However, while this leads to good drivers 

receiving lower premiums, bad drivers may be relegated to a class of “uninsurables” 

who are unable to get insurance at any premium. In the past, these drivers would have 

been placed into a larger risk pool, where their higher risks may be offset by others 

with a lower risk. Equity considerations and protections must be incorporated in using 

data to create beneficial outcomes for the economy and society.

Equitable access to IoT for small businesses. Small businesses are the heart of 

American commerce and stand to benefit from the integration of IoT into their 

businesses. However, these small businesses lack the staff and technical expertise, 

resources, and the funds to afford and buy and integrate these IoT technologies. For 

example, many small farming businesses have limited appetite and funds to invest in 

IoT technologies with an “unknown” outcome. Instead, they prefer to invest those 

funds into inputs (seeds, fertilizer, herbicides, etc.) which they know will lead to 

something tangible (“produce”) even if it was produced inefficiently. Similarly, small 

retail businesses have limited free cash available, and prefer to invest that limited in 

inventory which they know will convert to profits. These day-to-day realities “trap” 

many small businesses into an endless cycle and hinders their ability to buy and use 

IoT to obtain its associated benefits. 

Equitable access to opportunities for small business and start-up IoT innovators.

Start-ups and other small businesses create many of the innovations that bring 

disruptive new value to the economy and society and keep America strong and 

resilient. However, many of these companies face challenges in bringing these 

innovations to reality. For example, many businesses and government agencies are 

often unaware of these innovations and have limited funds, policies and processes 

ability to evaluate and validate them. Innovations often face the “valley of death” from 

successful completion of pilot or proof of concept to contract. Procurement policies 

and processes, designed for well-established mature products and services, do not 

work well for innovative solutions. As a result, many innovative offerings from small 

businesses and start-ups fail not because of their offering, but because they face 

access barriers to market that larger businesses don’t have. 

Equitable access to workforce development and employment opportunities. The 

integration of IoT into the economy and society creates new types of jobs and 

employment opportunities. Some of these jobs will require new skills, while others 

may be extensions to existing skills. For example, some IoT jobs will require digital 

skills, such as integration, programming, cloud application development, 

cybersecurity and data science. At the same time, other jobs will be needed to 

manufacture, install, service and maintain IoT devices and IoT-enabled equipment. 
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These employment opportunities are at risk of bypassing socioeconomically 

challenged and rural communities, whose residents may not have the language 

proficiency, digital literacy, access to education and development opportunities, and 

broadband service, to be included. Labor shortages exist in many industries today and 

hinders the American economy. Similarly, the inequitable access to employment 

opportunities created by IoT will hinder the country’s full realization of the economic 

and societal benefits. 

Finding: Small businesses can reap significant benefits from IoT, but 

significant barriers hinder adoption.

Supports Recommendation(s) x.x, x.x

IoT brings significant value and outcomes for both small and large businesses. Small 

business enterprises lack the resources and scales of economy that their larger 

counterparts have, and the adoption of IoT into their operations can have a significant 

and immediate impact. For example, soil moisture sensors help farmers direct 

irrigation to those specific areas where the soil needs watering most. Small farming 

operations are cash flow constrained, and the money saved on watering can be 

immediately redeployed to help pay for other things. In manufacturing, IoT sensors 

continuously monitor the condition and performance of production equipment, 

helping factories optimize production, reduce scrap, and minimize unplanned 

downtimes. This has an immediate impact on small factories, helping them to meet 

customer commitments, expand their business and profits, and overcome cash flow 

constraints.

A number of barriers hinder the adoption of IoT in small businesses. These include:

• Financial. The initial cost associated with purchasing and implementing IoT 

solutions may be beyond the means of small businesses. These businesses have 

limited financial resources, and many have cash flow constraints, hindering 

their ability to invest in IoT, hire skilled resources or contracting with service 

providers.

• Skills and Expertise. Integrating IoT technologies into existing business 

processes can be complex. Small businesses lack personnel with the expertise 

to successfully deploy and manage the integration. They face challenges in 

finding and retaining these employees. Training existing staff or hiring skilled 

workers can be difficult due to budget constraints and market competition for 

the same talent.
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• Infrastructure. Small businesses often lack the infrastructure to support the 

integration, operation and scaling of IoT. Existing infrastructure may need to be 

modernized. Networks may require upgrading to ensure consistent and stable 

connectivity for their IoT implementations. Software applications may be 

upgraded to integrate data from IoT sensors. Some businesses employ legacy 

systems, adding further complexity to integrate with IoT solutions.

• Cybersecurity and privacy concerns. Cybersecurity breaches are extremely 

disruptive to small businesses, who often lack the resources and expertise to 

implement and keep up with robust security measures, and mitigate the 

impacts of cyber-attacks. The collection of data from sensors adds further 

complexity. Small businesses are concerned on how their proprietary data is 

used and shared, as it is their source of competitive advantage. They also lack 

the expertise, knowledge and tools to navigate complex regulations and ensure 

compliance with data protection laws on customer data collected from IoT. 

• Limited Awareness. Many small businesses have very limited to no awareness 

and understanding about IoT solutions. These businesses have limited time 

and budget for exploring and staying updated on the latest technologies. Small 

businesses have limited exposure to industry conferences, trade shows, or 

forums where IoT trends are discussed. Many IoT solution providers focus their 

marketing efforts on larger enterprises, leaving small businesses unaware of 

available solutions that could benefit them. Small businesses may have 

difficulty finding relevant case studies or success stories that demonstrate the 

practical benefits of IoT in their specific context. 

• Adoption resistance. Small businesses, especially those in survival or growth 

phases, prioritize immediate operational needs over exploring new 

technologies. IoT may be perceived as complex and technical, especially by 

individuals who are not well-versed in IT. Small business owners and decisionmakers may feel overwhelmed by the technicalities associated with IoT, leading 

to a hesitancy to explore further. Small business owners may be unfamiliar with 

the potential advantages of IoT technologies and may hesitate to invest 

without a clear understanding of the return on investment. Misperceptions 

about the cost of adopting IoT technologies discourage exploration and 

investment in IoT solutions.

Finding: Small companies and startups are instrumental in developing 

many innovative and disruptive technology solutions and services, but face 

a variety of barriers in getting adoption.

Supports Recommendation(s) x.x, x.x
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Many disruptive technology and market innovations come from small companies and 

start-ups. However, start-ups face a variety of challenges in developing and bringing 

innovative offerings to market. As a result, many promising innovations never reach 

commercialization. Some of these challenges include:

• Access to Funding and Investment. Securing funding is challenging for IoT 

start-ups and small businesses. Funding is necessary for the research and 

development of innovative offerings, but investors are risk-averse when it 

comes to “unproven” and emerging technologies. Customers have limited to 

no budgets for funding pilot and proof of concept projects. While larger and 

established companies can afford to fund development projects and do free 

pilots, smaller companies and start-ups cannot. Many more start-ups and 

smaller businesses fail to navigate the “Valley of Death” (the period between 

initial successful pilot/prototype development and contracting) because they 

are unable to secure the bridging funds.

• Customer procurement processes are not designed to purchase innovative 

offerings. Existing government and enterprise procurement processes and 

policies are designed for sourcing established and mature products from 

established companies. These processes are not well-suited to buy “risky” 

offerings from start-ups with limited to no proof of performance, limited 

operating history, and innovative commercial models. Some larger companies 

address this by offering deep discounts or free proof of concepts to alleviate risk 

concerns, but small companies do not have the luxury to do so.

• Legacy regulations and standards. Certain industries, such as energy, 

healthcare and transportation, are subject to regulations and standards that 

were established for legacy systems and operations. The capabilities offered by 

IoT and other disruptive emerging technologies may deliver the desired 

outcomes in innovative ways, but may do it in ways that conflict with these 

existing industry standards and regulations. For example, drones are subject to 

FAA regulations specifying one drone, one operator. In addition, drones must 

operate within the line of sight of the operator. This prevents the development 

and operation of autonomous drones in farming, where drones could be used 

to collect imagery information of plant health, or conduct crop spraying.

• Market incumbents. Many start-ups offer technologies and solutions that 

disrupt and compete against existing incumbent legacy solutions. Incumbents 

are well established, and hinder market adoption of innovative solutions in a 

variety of ways. This includes limiting access to infrastructure and systems and 

creating “walled garden” ecosystems. For example, one equipment 

manufacturer “maliciously complies” with an industry standard for 
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communications, but encrypts the data traffic going through it, which 

effectively blocks access to the data by other machines. 

• Low market awareness. At this early stage, there is very limited market 

awareness of innovative IoT technologies and solutions. Start-ups often invest 

considerable resources and time to establish credibility and educate their 

target market about the technology, approach, benefits and value proposition 

of their innovative solutions. In addition, many start-ups lack the market 

credibility compared to larger and more established companies. Government 

adoption and use of innovative IoT solutions helps start-ups establish 

credibility, and more importantly, credibility of IoT. 

Finding: IoT enables new innovative business models which requires new 

business and technology platforms and ecosystems to support and scale 

it.

[Update with information from TomKat’s findings and opportunities.]

Finding: Interoperability is a key challenge for IoT across multiple 

industries.

Supports Recommendation(s) x.x, x.x

Interoperability allows heterogeneous devices and systems to integrate, 

communicate and share information with each other and automate. For example, 

information collected from one IoT device is used as input data by another different 

device, or devices from different brands may communicate and work together in a 

system. While interoperability is enabled by standards, it is challenging to achieve for 

a variety of reasons. In some areas, IoT technology is still new and rapidly evolving. 

There are many areas of IoT technology to be standardized and attaining agreement 

on a standard takes time. While open standards provide the potential for seamless 

interoperability, the current market is filled with products with proprietary standards, 

“walled garden”78 device ecosystems and differing international standards and 

protocols. Some vendors believe their proprietary standard is technologically superior, 

some were first to market before standards developed, while others are concerned 

with commoditization of their offerings. For IoT to evolve, interoperability and 

78 A “walled garden” ecosystem is one in which a vendor or a group of vendors together form an ecosystem 

where their products are compatible with each other.
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standards across devices, industries and countries are critical. (source: NIST IoT report 

draft)

Finding: A variety of connectivity challenges is hindering IoT adoption, 

operation and scaling.

Supports Recommendation(s) x.x, x.x

The availability of connectivity service coverage is a necessary prerequisite for IoT 

adoption and operation. The COVID-19 pandemic highlighted the impact of the 

digital divide and the need for connected communities. Several government and 

private sector initiatives offer the potential to make connectivity ubiquitous. For 

example, a portion of the $65 billion in the federal Bipartisan Infrastructure Law will 

build infrastructure in underserved areas. California is building a $6 billion middle mile 

fiber network to facilitate the creation of last mile services to underserved areas.79 The 

FCC is considering the potential use of the frequencies in the TV white space for 

connecting IoT devices over wide expanses of rural areas. Several satellite operators 

are planning or have launched next generation Low Earth Orbit (LEO) broadband and 

IoT connectivity services to rural and underserved areas. These initiatives are 

supplemented by private enterprises establishing LTE and 5G private networks to 

connect campuses, factories and other facilities augment commercial 

telecommunications services. (source: NIST IoT research report draft)

Despite these efforts, more work needs to be done to overcome the various 

challenges IoT adopters and operators face. These include: 

• Lack of fixed and wireless connectivity infrastructure. While urban areas 

have the infrastructure to offer different connectivity service options, rural areas 

and remote regions lack the same. This may be manifested in the lack of fiber 

infrastructure, as well as a lack of sufficient wireless infrastructure. Limited 

infrastructure, low population and population densities, terrain challenges and 

poor economic returns limit industry connectivity investments in these areas. 

• Future use cases require higher bandwidth symmetric services. Future IoT 

use cases, such as drone and remote machinery operation applications in 

agriculture, require higher bandwidth symmetric connectivity services. The 

FCC’s current 25/3 broadband service level definition is insufficient to support 

those applications. 

79 State of California Middle-Mile Broadband Initiative, 
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• Insufficient spectrum to support future needs of IoT at scale. As the number 

of devices and IoT-enabled services continue to grow, additional wireless 

spectrum is needed to minimize performance issues. These issues include 

interference, latency, quality of service and reliability. IoT devices supporting 

first responder and medical applications, are especially vulnerable. Urban and 

metropolitan centers, having a large number of building structures, high 

wireless device density, are most susceptible to disruptions and issues. 

• Sunsetting of connectivity technologies. There are millions of IoT devices that 

are connected through 2G and 3G networks in the United States. As 4G and 5G 

networks enter into service, these older networks are turned off or “sunsetted” 

over a period of time. For example, the various carriers started turning off their 

2G networks between 2017 (AT&T) to 2022 (T-Mobile). Similarly, carriers turned 

off their 3G networks between 2021 and 2022.80 In many cases, it is not possible 

on a practical basis to replace and update the transmitters in the devices to 

newer protocols, rendering the devices useless. Managing the sunset and 

replacement of the devices is a major task and cost burden for IoT users and 

owners.

Finding: A lack of trust in IoT is a major barrier to widescale adoption. 

Supports Recommendation(s) x.x, x.x

The IoT raises several cybersecurity and data privacy concerns. Cybersecurity is top of 

mind with developers, adopters and privacy advocates. IoT devices expose new attack 

surfaces that can be exploited to enter the network, steal information and disrupt 

operations. Data collected from IoT devices can be stolen, improperly accessed, or 

used for purposes outside its initial design. Algorithms can be biased or tricked to 

produce incorrect or unintended outcomes. While interoperability, connectivity and 

compute provide the technical infrastructure for IoT to scale, a trust infrastructure is 

necessary for IoT market adoption to evolve and scale. 

Building trust and transparency is imperative in the IoT ecosystem. Initiatives like 

Privacy Transparency for IoT aim to make privacy practices more visible and 

understandable to consumers. In specific applications such as automobiles, 

introducing IoT Privacy information on Automobile Monroney Stickers and Location 

Tracking Notice in IoT e-labeling are key measures to inform consumers about the 

privacy features of IoT-enabled vehicles.

Link

omplete Overview of 2G & 3G Sunsets,” A. Worth, 1OT, August 29, 2019. Link
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Envisioning Privacy in the Internet of Things (IoT) Era

Supports Recommendation(s) x.x, x.x

As we delve deeper into the digital age, the Internet of Things (IoT) 's impact on privacy 

brings exciting opportunities and significant challenges. A comprehensive vision to 

address privacy in the IoT realm is critical, encompassing various aspects such as 

regulation, policy, trust and transparency, security, compliance, and education and 

innovation.

Regulation 

Central to this vision is the support of robust regulatory frameworks. The endorsement 

of a Comprehensive Federal Data Privacy Regulation is vital to setting uniform privacy 

standards across the United States. Furthermore, developing a Federal IoT Privacy 

Policy Framework is crucial to provide specific guidance for IoT technologies. Equally 

important is the Inclusion of IoT in Federal Privacy Regulations, ensuring 

comprehensive consumer protection under privacy laws.

Policy 

Policies form the foundation of privacy in IoT. Implementing Plain Language in Privacy 

Policies is essential to make privacy terms understandable for consumers. 

Additionally, well-defined Third-Party Data Sharing Policies are necessary to regulate 

the sharing and use of IoT data, thus protecting user privacy. In specific applications 

such as automobiles, introducing IoT Privacy information on Automobile Monroney 

Stickers and Location Tracking Notice in IoT e-labeling are key measures to inform 

consumers about the privacy features of IoT-enabled vehicles.

Security and Compliance

Security and compliance in IoT require a multifaceted approach. Universal Opt-Out 

Signals for IoT offer consumers a simple method to control their privacy settings. 

Promoting Privacy-Enhancing Technologies (PETs) is crucial for advancing secure IoT 

solutions. Adhering to NIST Sanitization Standards for Used Automobiles and 

Government Automobiles Resell also ensures proper data erasure before vehicle 

resale. Under this umbrella, 'Privacy by Design' for IoT is essential. This approach 

integrates privacy considerations into every stage of IoT product development, 

ensuring that privacy safeguards are built into IoT technologies from the ground up.
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Education and Innovation

Finally, educational initiatives for the IoT-savvy workforce are key to providing 

professionals with the skills and knowledge necessary to navigate and influence the 

future of IoT and privacy. This education will drive innovation, ensuring privacy 

considerations evolve alongside technological advancements.

This vision for privacy in the IoT era aims to establish a balanced ecosystem where 

innovation thrives alongside robust consumer privacy protection, achieved through 

comprehensive regulation, effective policies, enhanced trust and transparency, 

stringent security measures, and continuous education and innovation.

IoT has promised a revolution in connectivity and automation, offering immense 

potential for enhancing our daily lives and industries. However, a significant barrier 

hindering the widescale adoption of IoT technologies is the pervasive lack of trust. 

Trust is the cornerstone of any successful digital transformation, and without it, the 

promise of IoT remains unrealized. Trust in IoT must be addressed holistically through 

trusted devices, supply chains, data, partnerships, networks, digital threads, digital 

marketplaces, digital twins and business ecosystems.

The Importance of Trust in IoT

1. Begin with Trust81: Trust is fundamental to any technological advancement, 

including IoT. Without trust, consumers and businesses are reluctant to 

embrace IoT solutions due to concerns about data security, privacy breaches, 

and reliability. Trust forms the foundation that alleviates barriers to adoption 

of any technology and the basis upon which IoT ecosystems can thrive, 

fostering confidence among users and stakeholders.

2. Trust Trumps Technology82: Trust holds more significance than technology 

itself in the context of digital transformation. Trusting the devices, systems, 

and networks that underpin IoT is paramount to its acceptance. Despite IoT’s 

technological advancements, building trust is vital for its successful 

implementation. Trust in devices, systems, and networks is paramount to the

acceptance of IoT technologies.

3. The Significance of Digital Trust83: Digital trust is a critical factor in today’s 

digital age. IoT devices are central to digital transformation. Their reliability 

and security determine the degree of trust placed in them. Ensuring 

81 https://hbr.org/2020/05/begin-with-trust 82 https://www.industryweek.com/leadership/corporate-culture/article/21146077/trust-is-more-important-thantechnology-in-digital-transformation 83 https://www.mckinsey.com/capabilities/quantumblack/our-insights/why-digital-trust-truly-matters 
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trustworthiness is key to speeding adoption, proliferation and growth. 

Building and maintaining trust is essential, from manufacturers to end-users, 

as it unlocks IoT’s potential for informed decision-making, and innovation.

 

4. Holistic Digital Trust Framework84: Digital trust is the belief that digital 

technologies and the organizations behind them will safeguard everyone's 

interests and adhere to societal values. Recent failures in various digital 

domains have severely undermined trust. To address this, the World 

Economic Forum brought together tech giants, government officials, and 

consumer advocates to establish a framework for earning digital trust. This 

framework emphasizes leadership commitment to cybersecurity, privacy,

transparency, fairness, and other key factors to enhance trust in technology 

and the responsible use of new technologies. The Forum's report offers both a 

framework and guidance for building trustworthiness in technology 

development and deployment. 

Holistic Approaches to Building Trust in IoT

84 https://initiatives.weforum.org/digital-trust/about 
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• Trusted Devices85: Trust in IoT starts by creating awareness about 

trustworthiness of IoT devices. Device makers prioritize security, data 

protection, and standards, driven by the ""U.S. Cyber Trust Mark" which helps 

them differentiate. The mark fosters consumer awareness and trust 

simplifying identification of secure IoT devices. Recognition of the trust mark 

enhances consumer confidence and conveys devices are secure and trusted.

• Trusted IoT Partnerships: Building trust within IoT ecosystems involves 

establishing trusted partnerships. Collaborative relationships among 

stakeholders should prioritize data security, privacy, and adherence to ethical 

standards. Trustworthy partnerships contribute to the overall reliability of IoT 

solutions.

• Trusted Networks86: Securing Telco infrastructure and wireless networks, 

reinforced by encryption, authentication, and monitoring, are vital for trusting 

connected IoT devices and applications. Intrusion detection and network 

segmentation add extra layers of protection, instilling confidence in users and 

organizations. Trust in network integrity is key to preventing breaches, 

ensuring smooth operations, and driving IoT adoption.

• Trusted Supply Chains87: Ensuring the integrity of the supply chain is 

essential. Organizations should employ transparent and secure supply chain 

practices, from component sourcing to device assembly, to minimize the risk 

of tampering or vulnerabilities introduced during production. Digitalization, 

Blockchain and distributed ledger technologies are key enablers for creating 

trusted supply chains.

• Trusted Digital Transformation88: Digital trust in operations and business is a 

key enabler for IoT adoption. The role of trust in data privacy, cybersecurity, 

and ethical AI, emphasizing that trust-building is essential for successful 

digital transformations. Teams and organizations must prioritize trust through 

robust data protection, secure technology, and ethical practices to gain a 

competitive edge in the digital era. 

• Trusted Data for Privacy89: Emphasizing the protection of personal user data 

and privacy rights is key for trusting IoT. It involves compliance with stringent 

85 https://techcrunch.com/2023/08/23/the-us-cyber-trust-mark-finally-gives-device-makers-a-reason-to-spend-bigon-security/ 86 https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/cybersecurity-forthe-iot-how-trust-can-unlock-value 87 https://hbr.org/2020/05/building-a-transparent-supply-chain 88 https://www2.deloitte.com/xe/en/insights/topics/digital-transformation/digital-trust-for-future.html 89 https://www2.deloitte.com/xe/en/pages/about-deloitte/articles/securing-the-future/consumer-privacy.html
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data privacy regulations like GDPR and transparent data handling practices. 

Users have the right to control their data and its usage, necessitating clear 

consent mechanisms, robust encryption, and secure storage. Trust is essential 

to assure users that their data, including health information and personal 

preferences, won't be misused.

• Trusted Data for Confidentiality: Safeguarding enterprise data for IoT is 

critical to operations and competitiveness, including securing data transport, 

storage, access for devices and edge applications, etc. Confidentiality 

measures include encryption, access controls, secure communication, and 

identity management. Trust assures businesses that their confidential data 

will remain secure in all settings. 

• Trusted Digital Threads for Traceability: Digital threads are the backbone of 

IoT ecosystems, enabling traceability and transparency in data flows. Trust in 

these digital threads is crucial to ensure data integrity, accuracy, and 

reliability. Accountability and transparency across the entire IoT landscape 

depend on these trusted digital pathways. 

• Trusted Analytics and AI: Analytics and AI drive insights and decision-making 

in IoT applications. Trust in the data used for analytics and training models 

that drive AI algorithms and the algorithms themselves is paramount. Users 

need assurance that AI systems provide accurate, unbiased, and ethical 

insights. Building trust in analytics and AI fosters confidence in IoT's ability to 

deliver valuable outcomes.

• Trusted Digital Twins90: Digital twins serve as virtual replicas of physical 

objects, used in simulations, predictive maintenance, and more. Trust in the 

data used in digital twins is key for reliability and integrity. Users rely on real 

IoT data to represent real-world objects and situations, ensuring their 

usefulness and effectiveness in applications.

• Trusted Digital Marketplaces: In digital marketplaces, trust is vital for users to 

make informed choices. Trustworthy marketplaces offer transparent product 

information, user reviews, and secure transactions. Users need to trust that 

the products and services they find in digital marketplaces are of high quality 

and safe to use. 

90 https://www.mckinsey.com/industries/industrials-and-electronics/our-insights/digital-twins-the-key-to-smartproduct-development 
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• Trusted Business Ecosystems: Trust in business ecosystems requires 

organizations to invest in building and maintaining trust among ecosystem 

partners through ethical practices, transparency, and strong governance to 

foster trust91. Trust can be expanded as a fundamental part of ecosystem 

design that promotes collaboration, innovation and trust-based decisionmaking and the creation of trusted platforms. Industry stakeholders, 

regulatory bodies, and end-users should prioritize methods for trusted 

ecosystem.

In conclusion, the lack of trust poses a significant barrier to the widescale adoption of 

IoT technologies. As underscored by various sources, trust holds paramount 

importance in digital transformation, especially in IoT. To overcome this trust deficit, a 

holistic approach is imperative, encompassing trusted devices, supply chains, 

partnerships, networks, digital marketplaces, traceability using digital threads, digital 

twins, and business ecosystems. These elements must be fortified with security 

measures, traceability, and ethical practices. By addressing trust holistically, we can 

unlock the full potential of IoT and build a safer and more connected future. 

Finding: Artificial Intelligence (AI) is critical to unlocking and accelerating 

the value of IoT.

Supports Recommendation(s) x.x, x.x

Data collected from IoT devices is invaluable for creating insights and driving positive 

outcomes. For example, data from condition sensors is used to inform on the current 

status of an operational process or to diagnose a problem. Historical data may be used 

to identify trends and predict an outcome. Artificial intelligence automates the 

processing and analysis of vast amounts of data quickly and accurately. 

Some of this data is used to train and build machine learning (ML) and artificial 

intelligence (AI) algorithms. Once trained, these algorithms are deployed in the cloud 

or on the devices where they are used to analyze newly collected sensor data to 

generate insights, inform decisions and support autonomous actions. For example, 

cameras in fruit picking robots analyze images of fruit in a field and identify those ripe 

fruits for picking. 

Latency, connectivity and processing requirements determine where the algorithm 

resides on the device, local processing servers (“the edge”) or in the cloud. A current 

trend is that more and more algorithm processing is occurring on the device and the 

91 https://www.bcg.com/publications/2021/building-trust-in-business-ecosystems 
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edge, instead of the cloud. Facilitating this trend is the development of AI-capable 

semiconductors.

As more sensors and devices are deployed, the quality of the data used to train the 

algorithms improves, leading to more refined models, the extension of those models 

to more use cases and more accurate model outcomes. Continuing advancements in 

algorithm development create new models that service more complex and 

computationally intensive applications, as well as enable more efficient processing on 

existing resource constrained microprocessors. 

As connectivity and processing infrastructure expand, IoT will scale with new use 

cases that are ML/AI enabled. Continuing advancements in interoperability and 

development of low-cost devices will eventually lead to an environment with 

ubiquitous intelligence. This state, called ambient intelligence, is reached when 

intelligence is embedded and integrated transparently into the physical environment 

and human interactions. Intelligence, interoperability, connectivity and computing 

are interdependent. Developments in low-cost devices lead to more IoT devices, 

which increases the need for more connectivity service and coverage. As the number 

of devices scales, the amount of data collected grows. The need to process these data 

drives advancements in computing infrastructure and algorithms, to create 

outcomes. These outcomes increase the need for more devices to be integrated into 

the physical environment and the day-to-day interactions with humans. (source: NIST 

research report).

Artificial Intelligence (AI) Considerations

The IoT and Artificial Intelligence (AI) are two very distinct concepts that complement 

each other. When operational, IoT devices create and gather data. In turn AI analyzes 

the data to provide insights, interpretation, and decision making that can then and 

improve items on the IoT device such as its efficiency and productivity. Artificial 

intelligence (AI) can be defined as a collection of technologies and approaches that 

allow a machine to perceive its environment and take actions towards a specific goal.

It encompasses several different technologies that give computers human-like 

abilities of perception. 

Most of the AI systems today are machine learning (ML)-based systems, which allow 

computers to learn data patterns in a supervised or unsupervised manner, and then 

apply these learnings to make predictions, classify data, recognize objects or images, 

and understand speech or text. Other techniques that are often used in AI systems 

include deep learning (DL), natural language processing/understanding (NLP/NLU), 

computer vision (CV), and machine reasoning (MR)
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Within the manufacturing industry, AI is being used in a variety of environments. 

These range from the factory floor, where it improves the production and distribution 

of manufactured goods and enhances safety, to the back office, where it streamlines 

administrative tasks and bolsters customer service efforts. AI is also being 

incorporated into manufactured goods to allow others along the value chain, 

including distributor, retail, and service partners, to leverage the intelligence provided 

by the technology to provide better customer service. In addition, these partners can 

use AI to improve aspects of product design and lifecycle management.

IoT technologies in industrial markets together with components like sensors, data 

storage and integration, data analytics, and machine learning, can be applied to 

SCADA systems to improve interoperability and coordination among different 

machines. The sensors collect new data from various equipment and continuously 

feed the data into the analytics. This way, machine learning algorithms can learn from 

past data and fine-tune the settings on different machines for thousands or even 

millions of cycles to reach the optimal point of the entire system. The use of AI within 

the manufacturing sector is being driven by specific enabling market factors that 

include the digitization of data, the development of IoT networks, and the steady 

improvements in ML and DL algorithms. AI technology introduces scale and efficiency 

and is best applied to two types of problems:

1. Data analysis and subsequent predictive recommendations and actions: ML 

and DL technologies excel at analyzing massive datasets very quickly. They can 

complete data analysis computations much more quickly than manual human 

analysis or hardcoded computer analysis.

2. Routine, redundant tasks: AI technologies are successfully handling redundant, 

linear thought-focused tasks (clerical work, order taking, food service), freeing 

up human resources to focus on higher value, human-exclusive skills (creative 

thinking, problem solving, interpersonal skills, emotional intelligence, 

reasoning, negotiation, and decision-making).

Within specific vertical markets (manufacturing, health care, energy, and 

transportation) there are several use cases that leverage the power of AI to deliver ROI 

while employing ML, DL, NLP, and CV approaches that are commonly used across 

vertical segments. These use cases include:

• Digital Twins: A digital twin is a digital representation providing the elements 

and the dynamics of how a device or ecosystem operates and lives throughout 

its lifecycle. Digital twins combine sensor data with ML and software analytics, 

which are then used to create spatial graphs that provide a digital simulation 

model that is updated and changes in real time in tandem with their physical 

counterparts.
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• Energy Management: Within manufacturing, the consumption of energy 

remains a primary cost and concern for plant managers and the key decision 

makers of the company. While the cost of energy may be variable a company’s 

energy use is fully within its control. However, in order to better assess and 

control energy consumption within a manufacturing environment, machines 

must be equipped with sensor technology. Energy usage must be tracked at a 

granular level in order to assess key ratios, such as energy consumption versus 

productivity. The use of AI can make this tedious and data-intensive process 

much more efficient and effective.

• Medical Image Analysis: Analyzing images is a strong application for DL and 

CV within the realm of patient data processing. DL is now being applied to 

automate the analysis and increase the accuracy, precision, and understanding 

of images down to the pixel. Some of the more common applications include 

3D CV (images analyzed and rendered into detailed 3D models), auto grading 

of eye diseases, and detection and segmentation of radiology images.

• Safety Enhancement in Buildings: Employers have an incentive to ensure 

better compliance with safety standards and protocols. One example of how 

DL is being used to help ensure better compliance includes tools that allow 

employers to leverage photos and videos to identify workers who are missing 

hard hats, gloves, or other safety equipment.

• Street Lighting: Street lighting is an essential element for any city. In addition 

to providing better visibility for pedestrians and motorists, it adds a feeling of 

safety and security and can often deter criminal activity. Smart cities are adding 

AI capabilities to street lighting, which is designed to not only provide lighting, 

but also perform other tasks by incorporating CV, ML, and IoT connectivity. 

Streetlights can be equipped with an array of sensors to monitor traffic flow, as 

well as send signals to traffic lights and other traffic control devices. 

Manufacturers that have successfully incorporated AI technology generally have been 

able to achieve the following:

• An understanding of how analytics and AI can work together: Data analytics 

can and should be used to augment and support AI.

• An understanding of the goals and benchmarks needed to assess AI use cases: 

AI leaders need to be able to review the output from AI use cases and ensure 

that proper processes are in place for confirming or overriding questionable 

results. 

• A modicum of trust in AI: All stakeholders need to have confidence that AI can 

deliver benefits if properly deployed.
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• A strong culture of oversight: Regular oversight over the use of AI is critical to 

ensure that algorithms are delivering the benefits they should, while also 

remaining in compliance with applicable regulations, is a major key to success. 

Because the technology is still relatively new, stakeholders are much more 

likely to stay engaged if they are confident that there is proper oversight 

occurring on a regular basis. 

Generative AI

Traditional AI is trained on large data sets with human input, conversations, user 

queries and responses. Generative AI is trained on different sets of data to learn 

patterns to create content with predictive patterns. Generative AI can produce 

various types of content, including text, imagery, audio, and synthetic data. It is 

particularly valuable in creative fields and for novel problem solving, as it can 

autonomously generate many types of new outputs. ChatGPT, DALL-E, and Bard are 

examples of generative AIT applications that produce text of images based on usergiven prompts or dialogue. 

According to a recent McKinsey Global Survey 

(https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-aiin-2023-generative-ais-breakout-year), 2023 is listed as a breakout year for Generative 

AI. The survey describes the most commonly reported uses of Generative AI tools to 

be in marketing and sales, product and service development and service operations 

such as customer care and back-office support. Inaccuracy, cybersecurity, and 

intellectual property infringement are the most cited risks of generative AI adoption. 

As AI continues to move forward it’s important to note the distinction between 

traditional AI that and generative AI. Policies and regulations that are developed need 

to take this into account.

Finding: There is an insufficient number of people in the current workforce 

with the technical, digital and analytic skills required to develop, integrate 

and deploy, operate and maintain IoT devices and IoT-enabled systems and 

applications. 

A significant challenge in scaling IoT into the national infrastructure and economy is 

the development of a IoT ready workforce. The current workforce lacks many of the 

key digital, technical and data science skills and expertise required to support IoT. In 

addition, IoT involves the convergence of various disciplines, including information 

technology, data science, hardware development, and cybersecurity. Building an IoTready workforce requires a workforce with interdisciplinary knowledge who can 

understand the complexities of both hardware and software components. Integrating 

these diverse skill sets within a single workforce is a considerable challenge.
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The need for a more digital and technical skilled workforce is driven by:

• IoT requires different skills. Despite its connected nature, IoT is not IT. IoT is a 

disparate set of technologies requiring an interdisciplinary combination of 

existing and new technical, digital and analytic skills. The workforce must 

develop expertise in working with new connectivity technologies, such as 

LoRaWAN and 4G/5G, integration of IoT devices into internal and external 

networks, and the cloud. In addition, the workforce must develop skills in 

working with the cloud, and application development. Finally, the amount of 

data collected required data professionals to manage the data and analyze it 

to create optimal outcomes.

• Non-digital industries and systems go digital. Many pre-digital industries 

required limited technical and digital skills. For example, the installation and 

integration of HVAC systems into a building requires mechanical, electrical and 

ventilation expertise. However, smart HVAC systems incorporating IoT and 

other technologies now require technicians with networking skills to integrate 

them into the building’s IT network, and systems integration skills to 

interoperate with building and energy automation systems. Furthermore, 

smart HVAC systems collect vast amounts of data that must be studied by 

analytics-savvy operators to optimize occupant comfort and system 

performance, minimize operating costs and plan maintenance activities.

• The convergence of IT, OT and IoT systems. Industries such as manufacturing, 

energy and transportation employ operations technologies (OT), including 

supervisory control and data acquisition (SCADA) systems and programmable 

logic controllers (PLC), to monitor and control physical processes. On the other 

hand, business operations are supported by Information Technologies (IT) 

systems that process data and communications. In these industries, IT and OT 

systems operate independently of each other and are maintained by separate 

organizations. The incorporation of IoT into industrial processes require OT and 

IT systems to come together. This convergence requires a workforce with a 

specific set of digital skills, including understanding of IT and OT protocols and 

processes, cybersecurity, systems integration, cloud computing, programming 

and application development, IoT integration, data analytics. 

• The value of data analytics. IoT collects vast amounts of data that can be used 

to create beneficial and innovative outcomes. Unlocking that value requires a 

variety of skills, including data management and governance, analysis, and 

development of insights. In addition, there is a need for the development of 

algorithms and the application of machine learning and AI tools. While the 
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value of data analytics is understood, there is a current shortage of data savvy 

practitioners, analysts and scientists across all industries.

• Interdisciplinary collaboration. IoT involves the convergence of various 

disciplines, including information technology, data science, hardware 

development, and cybersecurity. Building an IoT-ready workforce requires 

individuals with interdisciplinary knowledge who can understand the 

complexities of both hardware and software components. Integrating these 

diverse skill sets within a single workforce can be a considerable challenge.

Finding: Many barriers to IoT adoption due to legacy infrastructure, 

security, and interoperability require multi-stakeholder platform-based 

business ecosystem partnerships that align business incentives on high 

value end-to-end solutions.

Supports Recommendation(s) x.x, x.x

Communication has been transformative for markets and illustrates the potential of 

connectivity. From carrier pigeons to marathon sprint, to paper, to newspaper, to 

telegraph, to telephone, to radio, to television, communication have been 

transformative and drove major market shifts92. 

Internet connectivity has been even more disruptive. It began with ARPANET 

followed by the world wide web, commercializing Internet, instant messaging, etc. 

Facebook and Twitter leveraged connectivity to develop scalable social platforms and 

reach huge valuations rapidly. However, unlike social platforms that leveraged the 

92 https://sci10sectionm.wordpress.com/2013/12/08/the-evolution-of-communication-effects-on-the-world-of-science/ 
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growing Internet infrastructure, it will be harder to evolve scalable IoT platforms on 

top of legacy hardware and software infrastructure. 

Foundational platforms accelerate evolution of technology ecosystems. History 

shows that innovative businesses can’t evolve in a vacuum. They must attract 

resources of all sorts, drawing in capital, partners, suppliers, and customers to 

accelerate growth through cooperative networks and ecologies of competition93. 

Hardware and software value chains evolve from foundational platforms (e.g. Intel 

Inside) into partnerships and scalable business ecosystems. 

Partnerships driven by connectivity gave rise to internet business platforms. Since 

the 90s disruptions, go market strategies, business platforms and revenue models 

advanced along with new generations of technologies on top of legacy infrastructure. 

In the new age of ecosystem partnerships94 value creation reflects a networked and 

dynamic collaboration and exchange among partners, which was accelerated with 

internet-based business platforms.

Platform-based business ecosystems created trillion-dollar valuations. Business 

scholars have advocated platform-based business ecosystems and their potential to 

fuel economic value driven by architecture, governance, and network effects95. 

Architecture platforms like Apple iOS and Android enable third parties to add apps to 

smart phones. Transaction Platforms like Airbnb and Uber enable supply-demand 

matchmaking for the exchange of goods, or services. Future Hybrid Platforms96

93 https://hbr.org/1993/05/predators-and-prey-a-new-ecology-of-competition 94 https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/ecosystem-partnering 95 https://sloanreview.mit.edu/article/platform-strategy-and-the-internet-of-things/ 96 https://sloanreview.mit.edu/article/the-future-of-platforms/
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combine the advantages of both. Collaborative platforms like MS teams and Zoom 

which grew rapidly during Covid-19, facilitate innovation, but not business 

orchestration. 

Multi-stakeholder collaborative business platforms failures offer lessons for 

strategy. The IBM-Maersk TradeLens blockchain platform was taken out of the 

market97 because it was not open and failed to gain stakeholder support in the 

maritime supply chain. Collaborative platforms and ecosystems emerge as new 

organizational forms that provide distinct ways to cope with market failures (e.g. 

fragmented supply chain) or organizational failures (e.g. silos). Distributional and 

functional failures arise from self-interested actions by members, undermining the 

overall value structure98. Recognizing these failures is crucial for designing effective 

collaborative multi-stakeholder platforms across the IoT value chain, as they can 

inform strategies to prevent or mitigate failures, create value, and accelerate 

adoption. 

IoT creates opportunities for digital collaboration of orchestrated business 

ecosystems. As noted before, IoT provides the potential to transform linear supply 

chains and silos workflows to dynamic value chains and workflows. Transformative IoT

platforms enable scalable business ecosystems99 where enterprises collaborate to 

provide coherent end-to-end solutions that benefit all stakeholders. Platform-based 

business ecosystems based on Digital Orchestration, Governance and Network 

Effects will fuel Digital Marketplaces to drive economic growth. 

Finding: Disconnected supply chains with multiple stakeholders involved 

pose IoT adoption barriers. Industry specific partnerships using IoT for 

augmented supply chain logistics reduce risks, speed adoption and fuel 

economic growth. I don’t understand this finding.

Supports Recommendation(s) x.x, x.x

Disconnected supply chains can be digitally connected by leveraging IoT technology 

for global supply chain logistics focused on tracking goods from design, production, 

distribution, delivery, and end use. The logistics process will consider varied levels of 

automation relative to the capability maturity of enterprises all the way up to 

digitalization of logistics workflows. 

97 https://www.theregister.com/2022/11/30/ibm_and_maersk_tradelens_shutdown/ 98 https://www.sciencedirect.com/science/article/pii/S0048733323001907?via%3Dihub 99 https://sloanreview.mit.edu/article/how-healthy-is-your-business-ecosystem/ 
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Logistics for tracking scope will extend to include provenance and traceability of 

physical objects and data linked to identifiers to deliver assets with trusted 

information and security for the benefit of suppliers, consumers, distributors, 

operators, logistics companies, businesses, and all stakeholders in the value chain and 

industry ecosystems. 

Varied levels of security and trust for traceability will be considered for enterprises and 

global markets, in ways that maximize national security and economic prosperity. 

Traceability scope will be extended with digital threads to regulate market preference, 

access, and usage of goods, enable trusted data producers/consumers, marketplaces,

and AI applications to fuel growth.

Platform-based business ecosystem partnerships for supply chain logistics tracking, 

monitoring, and risk management can significantly benefit vertical markets. In each 

market, these ecosystem partnerships leverage IoT technology to enhance supply 

chain visibility, transparency, security, and resilience, leading to increased efficiency, 

reduced costs, and improved customer satisfaction. Exampled of ecosystem 

partnerships and value include:

• Automotive Supply Chain Partnerships: OEMs (e.g., Ford, Toyota), IoT 

hardware providers (e.g., Bosch), logistics companies (e.g., DHL), data analytics 

firms (e.g., IBM Watson). OEMs integrate IoT sensors into vehicles and parts. 

Logistics companies track shipments using IoT-enabled containers and 

vehicles. Data analytics firms provide predictive maintenance insights. This 

partnership can optimize supply chain visibility, reduce inventory costs, and 

improve vehicle maintenance. 
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• Industrial Supply Chain Partnerships: OEMs (e.g., Siemens), IoT sensor 

providers (e.g., Honeywell), logistics and transportation companies (e.g., 

FedEx), industrial automation firms (e.g., Rockwell Automation). OEMs embed 

IoT sensors in machinery. Logistics companies offer real-time tracking of 

industrial goods. Automation firms use data for predictive maintenance. This 

partnership enhances supply chain efficiency, reduces downtime, and lowers 

operational costs.

• Healthcare Supply Chain Partnerships: Medical device manufacturers (e.g., 

Medtronic), IoT solution providers (e.g., Philips), healthcare logistics companies 

(e.g., UPS), telemedicine platforms (e.g., Teladoc). Medical device 

manufacturers incorporate IoT sensors for tracking. Logistics companies 

provide temperature-controlled transportation. Telemedicine platforms offer 

remote monitoring. This partnership ensures the safe and timely delivery of 

critical medical equipment and enhances patient care. 

• Communications Supply Chain Partnerships: Telcos (e.g., Verizon), IoT 

connectivity platforms (e.g., Sigfox), logistics and distribution networks (e.g., 

FedEx), supply chain visibility solutions (e.g., Savi Technology). Telcos offer IoT 

connectivity. Logistics companies use IoT for asset tracking. Supply chain 

visibility solutions provide real-time insights. This partnership enhances the 

management of communication equipment and ensures seamless 

connectivity.

• Maritime Supply Chain Partnerships: Shipping and maritime companies 

(e.g., Maersk), IoT sensor manufacturers (e.g., Inmarsat), maritime logistics 

firms (e.g., Kuehne + Nagel), weather monitoring services (e.g., The Weather 

Company). Shipping companies install IoT sensors on vessels and containers. 

Logistics firms offer real-time tracking. Weather monitoring services provide 

maritime weather forecasts. This partnership optimizes maritime logistics, 

reduces delays, and enhances risk management for cargo shipments and can 

be enhanced with digital collaboration and sharing of data across the 

maritime ecosystem100. 

• Consumer Supply Chain Partnerships: Consumer electronics companies 

(e.g., Apple), IoT device makers (e.g., Fitbit), e-commerce giants (e.g., Amazon), 

last-mile delivery services (e.g., Postmates). Consumer electronics companies 

integrate IoT in products. E-commerce platforms use real-time tracking. Lastmile delivery services provide precise delivery windows. This partnership 

100 https://thetius.com/wp-content/uploads/2023/10/Common_Interest_Report.pdf 
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improves customer experience, reduces returns, and minimizes shipping 

costs.

In each industry, these ecosystem partnerships leverage IoT technology to enhance 

supply chain visibility, tracking, monitoring, and risk management, ultimately leading 

to increased efficiency, reduced costs, and improved customer satisfaction. For more 

detailed information refer to the section on augmented supply chains. Many 

industries with associations serving common business interested and facilitating 

partnerships. By leveraging platforms creating network effects101 they attract new 

members, broaden ecosystem IQ and accelerate adoption. 

Finding: Digitalization of Enterprise Workflows is Foundational in Creating 

a Trusted Digital Thread for a Continuous Flow of Data Connecting 

Business Processes, Products, Assets, and Digital Marketplaces Across 

Value Chains. 

Supports Recommendation(s) x.x, x.x

As stated before, IoT provides opportunities to transform linear workflows and supply 

chains to dynamic value chains. 

Supply chain refers to the sequence of activities and processes involved in the 

production, distribution, and delivery of a product or service to consumers. It primarily 

focuses on the logistics and flow of goods and services, where IoT can accelerate 

adoption and add value in improving logistics, automation, and operational efficiency. 

Value chain refers to the entire range of activities from the conception of a product 

or service to its delivery to the end applications. It includes activities related to supply 

chain logistics, and more. It aims to identify and create value at each stage of the 

process and provide benefits to all stakeholders that can be realized with 

digitalization. Digitalization enables digital value chains. 

Enterprise Workflow Digitalization for operating functions (Sales, Finance, or 

Marketing) using tools for Customer Resource Management (CRM), Business Process 

Management (BPM) and Business Process Optimization (BPO). These tools are used 

for production planning, procurement, logistics, inventory management coupled with 

personnel databases. 

101 https://www.cornerstoneondemand.com/resources/article/why-network-effect-secret-formula-your-associationssuccess/ 
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Trusted Digitalization extends the business process change to design and 

manufacturing creating products, assets with data linked to operations. Trusted 

Workflow Management (TWM) can be used to trace and tag users, tasks, data, logs 

and digital assets to produce metadata and information that can be shared without 

sharing the proprietary data or IP of the enterprise. By digitalizing the receivables, 

workflow process, and deliverables, enterprises can participate in value chains, and 

ultimately digital marketplaces. 

Design, manufacturing, physical asset data IDs for part codes, SKUs, serial numbers, 

etc. can be furnished into a trusted (certified) Digital Thread used by data producers, 

consumers, and partners to share metadata and information about physical and 

digital assets and workflows about across value chains. Digital marketplaces enable 

consumers to send queries to producers about which offerings and related data to 

license and what value-add to create from it. 

Trusted Digitalization coupled with secure IoT technology can help trace the 

movement of assets and data across supply chains, provide transparency to 

stakeholders and ensure that any information related to products and services is 

readily available and can be shared securely with relevant parties. Secure enterprise 

digitalization as discussed in this proposal to NIST102 is essential for multi-stakeholder 

collaboration on supply chain traceability security and resilience. 

Digitalization coupled with Digital Transformation is key for accelerating IoT 

adoption. Digitalization enables automation of manual processes and collaboration 

among suppliers and consumers. Digital platforms automate order processing, device 

onboarding, in-field monitoring, and predictive maintenance during field use which 

102 https://www.nist.gov/system/files/documents/2022/04/25/04-25-2022-GSA_TIES.pdf 
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results in increased efficiency, reduced operating costs and higher value XaaS 

(Anything as a Service) business models.

Finding: Digital transformation combining digitalization and 

organizational changes enables IoT product suppliers to become smartconnected suppliers offering new IoT applications and solutions that drive 

something-as-a-service revenue streams. 

Supports Recommendation(s) x.x, x.x

Digital Transformation involves a business process change through Digitalization and 

organizational changes to enhance IoT operations, customer experiences, 

competitiveness, process optimization and innovation. Suppliers of Industrial IoT

products can become smart-connected suppliers by digitalizing their operations and 

updating functions and processes. For example, IT organizations will transform from 

a support function to a value-add function. 

Digital transformation for Industrial IoT extends the business process change for 

suppliers to become high value smart-connected suppliers to their customers via 

their products. This may require an upgrade of the enterprise ordering and 

procurement infrastructure to enable data traceability and confidentiality for the 

enterprises of both suppliers and customers. 

Evolving legacy IoT suppliers into smart-connected IoT suppliers drives economic 

value. In industrial IoT an order of an IPC, PLC or SCADA device starts a process for 

Just-in-Time (JIT) assembly followed by procurement. Remote updates are not typical. 
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With digitalization secure IoT devices can be onboarded to the customer’s 

environment and connect via gateway to the supplier. Onboarded devices produce 

trusted data that can be shared between supplier and customers though a digital 

platform. This closed loop of trusted and secure data exchange enables several 

benefits that accelerate adoption: 

• Improved visibility and transparency through integrated data sharing, 

facilitating better inventory management and demand forecasting. 

• Real-time monitoring and analytics of production processes, for 

identification of inefficiencies and the optimization of workflows that lead to 

enhanced productivity. 

• Use of trusted data for AI-enabled digital twins to ensure accurate 

simulations, timely predictive maintenance and better process optimization 

boosting operational efficiency.

• Growth of XaaS103 revenue streams though value-added services and 

solutions, leading to stronger customer relationships and scalable economic 

value with partners.

Digital transformation is complex and requires leadership to drive economic 

growth. Many industrial companies have been slow to embrace digitization, but 

digital leaders who invested in automation and e-commerce have outperformed their 

peers in terms of revenues and total returns to shareholders. Digital transformation104

provides a first-mover advantage in the industrial sector and has been proven to 

facilitate a successful end-to-end solutions that encompass culture, organization, and 

technology systems, ultimately improving services for a diverse customer base. 

Industrial digital transformation is a shifting market landscape with constant 

disruption, affecting several functions, digital technologies and business models for 

large organizations that strive to drive growth and efficiency. Deloitte has published 

as collection of topics on Digital Industrial Transformation105 that executives can use 

to accelerate adoption and growth. 

103 https://www2.deloitte.com/us/en/pages/consulting/solutions/xaas-everything-as-a-service-model.html 104 https://www.mckinsey.com/industries/industrials-and-electronics/our-insights/implementing-a-digitaltransformation-at-industrial-companies 105 https://www2.deloitte.com/us/en/insights/focus/industry-4-0/digital-transformation-in-the-age-of-industry-4-

0.html 
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Finding: Slow adoption of enterprise digital transformation is the main 

barrier to IoT adoption. Phased approaches toward creating a Digital First 

Business are emerging that leverage industry ecosystem partners to drive 

economic growth.

Supports Recommendation(s) x.x, x.x

As stated before, in 2021, McKinsey & Co. revised downward the 2014 projection about 

IoT growth stating to The IoT has faced headwinds related to change management, 

cost, talent, and cybersecurity, and slow market adoption of digitalization and cyberresilience in enterprises. 

Enterprises are starting to implement Digital transformation in phases. Market 

research firm IDC suggests that digitalization has started. In phase 1.0 enterprise test 

various use cases experimenting with digital technologies. In phase 2.0, they develop 

new XaaS business models focusing on driving repeatable ROI. Finally, they extend 

the traditional value chain by working with ecosystem partners to become a digital 

first business to boost growth and profitability.

To accelerate revenue growth, enterprises develop industry ecosystem 

partnerships in line with their business needs by solving key problems in their 

industry. Industry ecosystems must have a core mission, and business incentives for 

companies to work together. The fundamental pillars of ecosystems include shared 

data insights, shared applications and shared operations and expertise106. 

106 https://www.idc.com/promo/future-of-x/industry-ecosystems?tab=one 
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Trusted industry ecosystems evolve from two key core competencies Resources & 

Data to maximize collective IQ output and Methodology & Technology to maximize 

operating efficiency. 

Resources & Data bring several parties collaborating in Private-public 

partnerships (PPPs) including, trusted networks, consortia, supply chains, 

government organizations, cloud services and digital marketplaces providing shared 

operational intelligence. PPPs accelerate the creation of data ecosystems107, which are 

vital for growth of digital businesses generating high margin recurring revenue 

streams. Many ecosystems focus on the provision of data: exchange, availability, and 

analysis. Incumbents seeking to excel in these areas must develop the proper data 

strategy, business model, and architecture108 to create services that improve customer 

relationships, lift adoption barriers, and secure strong positions through economies of 

scale.

Methodology & Technology help harmonize stakeholder orchestration, 

collaboration, data sharing and governance across supply chains or value chains by 

using adjacent technologies like blockchain, cybersecurity, ML/AI and digital twins 

enabled by trusted digital threads to maximize the value for all. Harmonization takes 

ecosystems to the next level109 in creating value by consolidating supply chains 

horizontally across sectors and strengthening touchpoints along value chains 

vertically. Participants collaborate and incentivize each other, fostering innovation 

and efficiency improvements across business ecosystems. Traditional companies 

need to expand beyond their historical industry boundaries to serve customers 

comprehensively. Multiple sectors, including B2B services, mobility, travel, health, and 

housing, are transitioning into vast ecosystems, potentially forming a $60 trillion 

integrated network economy by 2025.

Multi-stakeholder orchestration and business platforms should consider how 

ecosystems can integrate capabilities or IoT and AI, for circular economies, and cope 

with challenges related to value creation, regulation, and misinformation. To speed 

adoption the US government should consider the creation of an office for emerging 

technologies, IoT, 5G+, AI, Blockchain, and Quantum Computing, as stated in an earlier 

finding and commentary. 

107 https://www.bcg.com/publications/2018/how-internet-of-things-iot-data-ecosystems-transform-b2b-competition 108 https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/tech-forward/data-ecosystems-madesimple 109 https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/ecosystem-2-point-0-climbing-to-the-nextlevel 
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Finding: Convergence of AI and IoT plus adjacent technologies and 

platforms serving circular supply chain ecosystems will accelerate 

sustainability and drive disruptive growth fueled by massive data centers 

in a hyperconnected planet. 

Supports Recommendation(s) x.x, x.x

The global economy operates linearly, extracting, producing, consuming, and 

disposing of materials, posing challenges due to finite resources. Transitioning to a 

circular economy, where resources are recovered and recycled, has been elusive but 

offers trillions in value. Barriers include low residual product value, material collection 

challenges, high processing costs, and supply chain traceability and monetization 

issues. AI and IoT platforms collapse these barriers110. 

IoT is the body and AI is the brain, supply chains & networks are the arteries where 

data flows. Orchestrated AI + IoT (AIoT) platforms linking smart-connected suppliers 

with smart-connected environments powered by massive data centers will create 

digital marketplaces and sustainable ecosystems, which will surpass human 

intelligence in a few decades. AIoT and data are intricately interconnected in a circular, 

rapidly evolving technological landscape111: 

1. Data and IoT: IoT devices generate vast amounts of data through sensors and 

connected devices, including temperature readings, location information, and 

user interactions. This data can be stored and analyzed to gain insights and 

make informed decisions, such as optimizing energy usage or monitoring 

machinery health.

110 https://hbr.org/2023/06/how-ai-will-accelerate-the-circular-economy 111 https://www.linkedin.com/pulse/transformative-power-data-ai-iot-shaping-worlds-future-jha/ 
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2. Data and AI: AI relies heavily on data with machine learning algorithms 

requiring extensive datasets for training. Once trained, AI models can analyze 

and interpret data for tasks like natural language processing and predictive 

analytics, extracting valuable insights and patterns that may be too complex 

for manual analysis.

3. AI and IoT: AI enhances IoT systems by processing and analyzing real-time 

data from IoT devices. For instance, AI algorithms can detect anomalies, 

predict equipment failures, or optimize resource allocation in smart cities. AI 

empowers IoT systems to make autonomous and intelligent decisions based 

on the data they collect.

The convergence of IoT and AI will drive high value solutions across industries.

Data is the new raw material or the “new oil” for AI, which, in turn, can be applied to 

analyze and extract valuable insights from the data generated by IoT devices. This 

synergy between data, AI, and IoT coupled with quantum computing powered by 

massive data centers will drive advancements across various industries, including 

healthcare, manufacturing, transportation, and smart cities.

• Smart Cities: Implement AI-powered analytics on IoT sensor data to optimize 

traffic flow, waste management, energy usage, and public safety in urban 

environments.

• Predictive Maintenance: Use AI algorithms to analyze IoT data from industrial 

machinery and equipment to predict maintenance needs, reducing 

downtime and improving operational efficiency. 

• Healthcare Monitoring: Combine IoT wearables with AI-powered analytics to 

monitor patients' health data in real-time, enabling early detection of health 

issues and timely medical interventions.

• Supply Chain Optimization: Employ IoT sensors to track goods in transit and 

use AI to predict potential disruptions, enhancing supply chain visibility and 

reducing inefficiencies.

• Precision Agriculture: Utilize IoT devices to gather data on soil moisture, 

weather conditions, and crop health, then apply AI algorithms to optimize 

irrigation, planting, and harvesting. Utilize sensors and analytics to measure 

spoilage in storage and distribution.
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• Energy Management: Integrate AI algorithms with IoT-connected devices to 

optimize energy consumption in buildings, adjusting lighting, heating, and 

cooling based on occupancy patterns.

• Connected Vehicles: Use IoT sensors in vehicles to collect data on driving 

behavior and road conditions, then apply AI to improve road safety, traffic 

management, and vehicle diagnostics.

• Environmental Monitoring: Deploy IoT devices to collect environmental data 

(air quality, water levels, etc.), and employ AI to identify trends and potential 

hazards.

• Smart Homes: Integrate IoT devices like smart thermostats, cameras, and 

appliances with AI to create intelligent and automated home management 

systems.

• Wearable Health Tech: Combine IoT wearables with AI-driven analytics to 

provide personalized health recommendations based on continuous 

monitoring of vital signs.

• Industrial Automation: Use AI to analyze data from IoT sensors in 

manufacturing processes, optimizing production, quality control, and 

resource utilization.

• Natural Disaster Management: Combine IoT sensor networks with AI 

algorithms to predict and manage natural disasters, such as flood monitoring 

and early warnings.

• Agricultural Automation: Use AI and IoT to automate tasks like planting, 

watering, and harvesting in agriculture, leading to increased crop yield and 

reduced labor costs.

• Energy Grid Optimization: Utilize IoT-enabled smart meters and AI 

algorithms to balance energy demand and supply, improving efficiency and 

reducing costs.

• Waste Management: Combine IoT sensors on waste bins with AI analytics to 

optimize waste collection routes and schedules, reducing fuel consumption 

and operational costs.
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• Consumer Electronics: Infuse AI capabilities into IoT-connected consumer 

electronics to create intelligent devices that can learn user preferences and 

adapt their behavior. 

• Smart Appliances: Integrate AI and IoT to create appliances that can interact 

with users, optimize energy usage, and provide real-time feedback on 

performance. 

Orchestrated platform ecosystems combining AI and IoT accelerate adoption and 

growth of digital economies. IoT produces data, AI consumes data, supply chains and 

networks transport data and data centers process applications to monetize data for a 

wide variety of use cases. Emerging trends in digital platforms include sustainability, 

connected manufacturing, creator economies, and new regulations112:

1. Integration of Artificial Intelligence (AI): AI is becoming integral to digital 

platforms, offering scalability, flexibility, better decision-making, and 

personalized processes. Some platforms will offer AI as a service, while others 

will adopt AI for their own operations. Challenges include addressing biases, 

labor issues, and equitable share of AI benefits.

2. Growth of Circular Platforms: Digital platforms will support circular 

economies by enabling product and material exchanges, promoting reuse, 

repair, redesign, and recycling. Opportunities include material exchanges, 

reuse/resale marketplaces, sharing assets (e.g., cars, real estate), circular 

supplier networks, and sustainable logistics. 

3. Varied Platform Regulations: Platforms face new regulatory oversight, with 

variations between geographic regions. For example, the US Section 230 

offers legal immunity for content posted by third parties, while the EU Digital 

Services Act requires transparency and holds platforms liable for violating 

terms of service.

4. Connected Manufacturing: Manufacturing is adopting digital technologies 

with platform-based solutions leveraging data for smarter factory operations, 

optimized supply and demand forecasting, and predictive analytics. This 

enhances supply chain visibility and competitive advantage. 

5. Increasing Power of Influencers and the Creator Economy: The creator 

economy, estimated at $100 billion, is driven by independent creators 

monetizing their activities. Influencers and creators face challenges like 

112 https://mitsloan.mit.edu/ideas-made-to-matter/5-trends-mit-platform-report 
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burnout and time management, with AI tools like ChatGPT offering assistance 

in saving time and managing workloads. 

The circular nature supply chains require trusted digital threads combining AI and 

IoT. Trusted digital twins and AI require trusted data produced by trusted devices. 

Trusted devices require trusted hardware and software bills of materials (HBOM and 

SBOM). Trusted HBOM require trusted design and manufacturing of physical assets 

that may be disposed on recycled. The convergence of IoT and AI has a potential to 

drive high-value sustainability platforms across circular supply chains for tracking and 

monitoring product utilization, analyzing materials to minimize waste, and increasing 

the use of recycled materials to reduce carbon emissions. 

The explosive growth of AI and IoT platforms require monitoring and regulatory 

actions: The above use cases are a fraction the vast potential combining AI and IoT 

platforms fed by data transported through supply chains or networks which may or 

may not be trusted. ChatGPT platform reached 100M users in a fraction of time 

compared to Twitter and Facebook and 2M developers creating a plethora of APIs and 

apps. Many of these developers rogue actors from adversary nations connecting 

remotely to AI platforms, so monitoring and regulating these platform ecosystems are 

key to mitigate risks and drive growth. 

Industry findings

Finding: Precision Agriculture. IoT brings significant value to agriculture, 

but adoption is slow.

Supports Recommendation(s) x.x, x.x

Agriculture is undergoing a transformation driven by the integration of information 

and digital communications technologies, the Internet of Things (IoT), data analytics, 

automation and robotics and other emerging technologies.113 This transformation 

offers the potential to increase agricultural productivity, operational efficiency, 

facilitate adaptation to climate changes and enhance overall competitiveness. IoT 

sensors on tractors, drones, and in the soil collect data on soil moisture, nutrient levels, 

and crop health. IoT-based irrigation systems monitor weather conditions and soil 

levels. Wearable IoT devices on livestock provide real-time data on animal health, 

113 “Agriculture 4.0: Broadening Responsible Innovation in an Era of Smart Farming”, D. Rose and J. Chilvers, Frontiers 

in Sustainable Food Systems, Dec 21, 2018. Link
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behavior, and location. IoT sensors in fields continuously monitor environmental 

conditions and provide data for predictive analytics.

The application of IoT to agricultural production and operations produces a variety of 

benefits, including increased efficiency, minimize and optimize the use of inputs 

(water, fertilizer, pesticides, and herbicides), improve crop and livestock production 

yields, reduce waste, and decrease costs and increase profitability. 

• Increased Efficiency. IoT helps farmers and ranchers become more efficient 

and productive. For example, the use of IoT to monitor animal health minimizes 

the need for workers to physically inspect the livestock on a regular basis. 

Sensors mounted on drones flying over large fields check plant health and 

quickly identify areas needing attention..

• Input Optimization. IoT devices help optimize the amounts of inputs (water, 

fertilizer, pesticides, and herbicides) to be used based on real-time knowledge 

of growing conditions and providing insights into the exact needs and 

application of inputs to maximize crop growth and health.

• Enhanced Yield and Quality. Agriculture is a data-driven business. The ability 

to monitor growing conditions, animal and crop health in real-time, along with 

analyzing the data collected, helps farmers identify and respond to issues 

earlier and more proactively. This facilitates crop and livestock production, 

leading to improved yields and less waste.

• Cost Savings. IoT yields cost savings by reducing and optimizing the use of 

inputs, minimizing livestock health issues, support automation, and reducing 

the number of workers needed to support operations. These cost savings 

increase productivity and improve profitability and cash flow.

● Story 1: IoT can help small family farms be productive and profitable

○ 2 million farms in US. 98% are family farms. Small family farms (gross 

income < 350K) are 90% of all farms, 48.8% of all farmland, and 21.1% of 

production

○ 62 - 81% of these small family farms are operating on < 10% margins

○ Production expenses have increased by 18% in 2022

● Story 2: IoT can help agricultural producers navigate around the impacts of the 

changing climate.
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○ Changing temps and precipitation patterns affect plant lifecycles, 

decrease crop yields, increase livestock stress and health, reproduction 

and milk and egg production

○ Corn yields have declined 3.8% and wheat yields have declined 5.5% 

(compared to no climate trends)

● Story 3: IoT can help increase agricultural production yields to support the 

upcoming food shortage

○ By 2050, UN estimates there will be a global food shortage

○ Increase in half percent in yield was enough to end starvation and 

famine in India (Green Revolution)

IoT in agriculture suffers from a variety of challenges. The top barriers include:114

• Connectivity. Agricultural producers face three connectivity challenges. First, 

there is very limited broadband infrastructure and Internet service in rural 

areas, and many agricultural producers lack “broadband to the farmhouse”. 

Second, while the FCC considers 25/3 Mbps (download/upload) service to be the 

broadband benchmark, this asymmetric level of performance is insufficient for 

precision agriculture needs which send large amounts of data, such as drone 

imagery and mapping data, to cloud data centers for processing and analyses 

to support critical decision-making in a timely manner. Finally, wireless 

connectivity service must be made available to the “last acre” to support 

agricultural activities. This is complicated by the size of farms and ranches, 

some of which span thousands of acres over diverse terrains.

• Digital skills. As digital and emerging technologies are increasingly integrated 

into agricultural equipment and operations, the skills that agriculture workers 

need to be successful will change. For example, as smart machines increasingly 

automate previously manual activities, agriculture jobs will evolve from being 

low skill repetitive physical work to medium to high skill non-repetitive digital 

work. New skills include data analytics, precision agriculture, robotics and 

automation, networking, and systems integration. 

• Interoperability. Farms have a variety of equipment, from the “latest and 

greatest” equipment with current technology to 30- to 40-year-old legacy 

114 Chan, B., Feller, G., Paramel, R., Reberger, C., 2022, September. Economic Research and Analysis of the National Need for 

Technology Infrastructure to Support the Internet of Things (IOT), Strategy of Things Sponsored by the National Institute of 

Standards and Technology
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equipment with limited technology and no connectivity. Interoperability 

challenges are a major barrier to IoT adoption and value realization in 

agriculture where old and new equipment need to coexist and work together. 

For example, some equipment may incorporate incompatible physical 

connections and require the use of adapters to communicate with other 

equipment. Others may have different formats (or syntaxes) for the same data, 

while others have different meanings for the data. Old equipment may not 

work with newer equipment, despite coming from the same manufacturer. 

• Adoption resistance. Despite the benefits of IoT and precision agriculture 

technologies and solutions, uptake of these solutions have been uneven and 

may take as long as 15 years for the technology to reach a critical mass.115 Large 

producers are more likely to adopt these technologies compared to smaller 

farms because they have more education, are less wary of technology and can 

support larger economies of scale.116 Some of these reasons, include the limited 

availability of broadband and connectivity in rural areas, “right to repair” 

concerns, trust in personal expertise over technology, and poor previous 

experiences with technology.

Need Ranveer and Nick content/stories here. Maybe use the story ideas I had supplied 

previously.

Finding: Smart cities and infrastructure. The development of smart cities in 

the United States is limited, uneven and slow to develop.

Supports Recommendation(s) x.x, x.x

IoT and its adjacent technologies offer the potential to transform cities and 

communities to become more responsive, resilient and sustainable. For residents of 

these communities, smart cities offer opportunities to improve quality of life, drive 

economic vibrancy, and increase public safety. Despite the potential for beneficial 

outcomes, current smart city efforts in the United States are small in scale, limited in 

scope and fragmented in nature. 

There are examples of IoT-enabled smart city applications in use today. These include:

• Smart streetlights employ LED bulbs, connected sensors and a controller to 

dim and brighten the streetlamps as needed. Smart streetlights also determine 

115 “Adoption of Farming Technology, Or Precision Ag, Varies Across Generations”, KTTN News, December 20, 2020. Link

116 “Adoption of Precision Agriculture”, USDA NIFA. Link
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if the lamp has malfunctioned, and notifies city staff immediately so that it can 

be replaced. 

• Smart parking employs either in-ground sensors or cameras to monitor 

parking space availability. Open spaces are communicated to drivers through 

a mobile app or digital signage on the street or garage. This helps drivers 

navigate to the space directly, instead of driving around looking. In addition, it 

also helps identify parking space violations and direct parking enforcement 

officers to the spot directly without having to drive around.

• Community air quality networks are deployed in select areas of the community 

to monitor environmental conditions and inform residents and policymakers. 

Air quality networks may be deployed in areas with poor air quality, or where 

poor air quality would harm vulnerable populations such as communities 

directly adjacent to freeways or industrial plants.

• Intelligent traffic management systems help manage the flow of traffic, 

minimize congestion and decrease accidents and injuries. For example, LIDAR 

or camera-based traffic analytics systems monitor “near misses” at 

intersections and inform traffic engineers of dangerous conditions to be 

addressed. 

• Camera systems employing AI and facial recognition algorithms help reduce 

crime and aid in the identification and capture of criminals. Images are 

captured and analyzed in real time by facial recognition software.

Despite the tremendous potential offered, smart cities have been slow to develop. This 

is attributed to a variety of reasons. These include: 

• Awareness and Vision. Many community and political leaders lack awareness 

of IoT and smart city technologies. Others lack the vision and the innovation 

culture to incorporate these technologies and capabilities into a city’s 

infrastructure and operations. 

• Lack of funding. Funding is one of the top issues holding back smart cities. 

These projects, at scale, is very expensive. While larger cities may have the 

capabilities and some funding vehicles to support these projects, America’s 

small and medium size cities do have very limited capabilities. In some cases, 

federal, state and regional grants may be available, but securing these grants 

can be difficult.

• Lack of skills and resources. Many cities and communities lack the new 

innovation and digital skills and resources to plan, deploy, operate and support 
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IoT applications. These resources are scarce in the market, and cities often 

cannot compete with the private sector for the same talent.

• Privacy Concerns. The extensive collection of data from IoT devices raises 

concerns about data security and privacy. Ensuring robust cybersecurity 

measures and transparent data handling practices is crucial to building and 

maintaining public trust.

• Community and political resistance: Candidates are not elected for building a 

smart city. Political leaders are re-elected if they are responsive to the needs of 

their constituents. Smart city initiatives that don’t align with the city’s strategic 

and near-term priorities are likely to face resistance from both citizens and 

policymakers. 

Smart Infrastructure

Infrastructure is essential to the functioning and resilience of the United States. For 

example, a nationwide network of roads, waterways, rail and airports transports 

freight and goods to market, and connects people with places. A regional system of 

natural and man-made reservoirs, aqueducts, pipes, pumping stations, and treatment 

plants brings fresh water to cities and farms. Electricity generated from renewable 

and non-renewable energy power plants travels over through a network of 

transmission lines and substations to power cities and communities across the 

country. Sewage is routed from homes and buildings through a regional network of 

underground pipes to wastewater treatment plants for reclamation for reuse and 

release.

Smart infrastructure integrates IoT and other digital technologies into physical 

infrastructure. This convergence enables new innovative capabilities for physical 

infrastructure and allows it to be managed, operated, and maintained more efficiently

and effectively. Sensors embedded into infrastructure, such as roads, building 

structures and machinery, monitor its condition in real time, notifying operators of 

abnormal conditions immediately so that it can be addressed before it becomes a 

hazard or lead to service interruptions. Data collected from the sensors are analyzed 

by algorithms to optimize performance and usage, predict maintenance needs, and 

extend infrastructure life. In addition, IoT data helps validate and improve engineering 

models, build high fidelity digital simulations, and facilitate managerial and 

operational decision-making. 

The benefits of smart infrastructure included optimized operations and decreased 

costs. For example, mechanical water pumps equipped with sensors monitor 

equipment conditions during operation. The sensor data is analyzed by algorithms to 
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determine when maintenance is actually needed so that the pumps can be 

proactively serviced, thereby ensuring continuous system operation and preventing 

cost escalation. Similarly, smart electrical grids employ sensors and two-way 

communications between utilities and consumers to monitor and manage power 

flows, and respond to changes in electricity demand. This ensures that the most 

appropriate energy sources, including renewable energy, batteries, and upstream 

generation plants, are utilized to meet demand while increasing grid resilience, 

reducing operational costs, and minimizing carbon emissions from upstream fossil 

fuel power sources.

Despite the many capabilities and benefits offered by smart infrastructure, American 

infrastructure is old and failing. It must be repaired, replaced, and upgraded before it 

can be digitized and made “smart”. The American Society of Civil Engineers (ASCE) 

have given American infrastructure an overall C- grade in its 2021 report card,1 a slight 

improvement from the previous report card (2017), which rated the state of American 

infrastructure as D+.2 For example, the United States has over 2.2 million miles of 

underground pipes that deliver drinking water. There is a water main break every two 

minutes and an estimated 6 billion gallons of treated water are lost each day.3 Many 

of America’s wastewater treatment plants were built in the 1970’s and have an average 

life span of 40-50 years.4 This aging infrastructure and inadequate capacity leads to 

the discharge of 900 billion gallons of untreated sewage into U.S. waterways each 

year.5

Another concern is the vulnerability of smart infrastructure to cybersecurity threats, 

cybercriminals, and malicious state actors. IoT and other smart technologies create 

new attack surfaces and vulnerabilities to assets and infrastructure that had 

traditionally not been digitized or had been protected through “air-gaps”. These 

cyberattacks may lead to disruption of operations and services, compromise of control 

and operational capabilities, and harm to millions of Americans who rely on this 

infrastructure. For example, the energy sector was the third and fourth most targeted 

sectors in 2020 and 2021 respectively.8 The utility industry averaged 736 cyberattacks 

per week and experienced a 46 per cent year-over-year increase in cyber-attacks in 

2021.9 In 2019, a renewable energy generator company, the largest private owner of 

operating solar assets in the United States, was subjected to a denial-of-service attack. 

While no loss of energy generation was reported in the attack, the company lost 

visibility into about 500 MW of wind and PV generation in California, Utah and 

Wyoming.10 Similarly, U.S. water utilities are prime targets for cyberattacks. The March 

2020 Cyberspace Solarium Commission report stated that the nation’s 70,000 water 

utilities “remain largely ill-prepared to defend their networks from cyber-enabled 

disruption.”11 In 2021, an operator at a small water treatment plant in Oldsmar, Florida, 

thwarted an attempt by an intruder to boost the level of sodium hydroxide (lye) in the 

water supply to 100 times higher than normal.12
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While the Bipartisan Infrastructure Law of 2021 provides funding to repair and update 

America’s infrastructure, it also represents a “once in a lifetime” opportunity to build 

an initial set of smart infrastructure and realize the benefits that it brings. 

- Some content on smart cities

- Some content on public safety

Finding: Transit and traffic: IoT is transforming transit systems and traffic 

management with real-time data analytics, intelligent traffic management, 

and predictive analytics to enhance efficiency, reduce congestion, increase 

safety, and improve overall transportation experiences.

Supports Recommendation(s) x.x, x.x

According to data from the National Highway Traffic Safety Administration (NHTSA), 

in 2022 an estimated 42,795 people died in motor vehicle crashes. While this latest 

estimate shows that roadway fatalities have remained flat after two years of dramatic 

increases, Transportation Secretary Pete Buttigieg states that “We continue to face a 

national crisis of traffic deaths on our roadways, and everyone has a role to play in 

reversing the rise that we experienced in recent years.” https://www.nhtsa.gov/pressreleases/traffic-crash-death-estimates-2022. Back in January of 2022, the DOT 

released the comprehensive National Roadway Safety Strategy, a roadmap to address 

the national crisis in traffic fatalities and serious injuries. One of the key actions in that 

roadmap includes leveraging technology to improve the safety of motor vehicles on 

our roadways. 

Smart traffic technologies provide an organized, integrated approach to minimizing 

congestion and improving safety on streets through connected technology. These 

technologies smooth traffic flows and prioritize traffic in response to demand in real 

time. They enhance pedestrian, bicycle and vehicle safety and reduce accidents that 

cause injuries and fatalities. Connected vehicles can alert drivers of potential hazards 

such as pedestrians crossing the street or other cars in the vicinity. Using adaptive 

control, detected vehicle congestion triggers changes to traffic signal timing to 

optimize traffic throughput in near real-time. Traffic signal timing can be adjusted to 

maintain schedules of bus and rapid transit lines. A path through the city is 

coordinated for first responder vehicles, using congestion data and vehicle location to 

adapt route guidance and traffic signal timing allowing these vehicles to get to their 

destination sooner.

These technologies can facilitate and support multimodal transit and other innovative 

transportation models (including ride-share, e-scooters, drones, etc.). They also 
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facilitate the safe testing and operation of automated vehicles (including cars, trucks, 

robotic delivery services, etc.). They can also reduce energy consumption by obviating 

stop-start driving that typically occurs at intersections. 

There is a large and growing ecosystem of public and private sector stakeholders 

deploying this technology that will redefine traffic safety. Some examples showcasing 

their benefits are provided below.

• A project to deploy Cellular Vehicle to Everything (C-V2X) in vehicles as part of 

an ongoing joint project with the Virginia Department of Transportation, the 

Virginia Tech Transportation Institute, and others to showcase the technology’s 

ability to improve work zone and intersection safety.117 

• A collaborative venture among an auto maker, school bus maker, and a school 

system that demonstrated C-V2X’s ability to protect children in and around 

school zones and bus stops.118 

• A project with an auto maker and a bicycle safety platform maker to highlight 

the benefits of C-V2X-powered bicycle use cases.119 

• A project with the Tampa Hillsborough Expressway Authority (THEA) to deploy 

and pilot Connected Vehicle (CV) applications to demonstrate safety and 

mobility benefits of the technology with respect to pedestrians in and around 

downtown Tampa.120

• A project with the Florida Department of Transportation (FDOT) to test and 

implement connected vehicle and pedestrian/bicyclist safety applications 

(active or passive) at 13 signalized intersections and 8 mid–block crossings 

within the core of the University of Florida (UF) campus.121

• The New York City Department of Transportation Traffic Safety Network. a 

large-scale Intelligent Transportation System (ITS) upgrade, replacing their 

entire citywide traffic communications network with a cellular IoT system. 

DOT’s traffic management system controls the traffic signals at 14,000 

intersections, as well as a range of ITS devices including traffic cameras, variable 

message signs and vehicle detection devices. The new network is highly 

117 Jacob Levin, “Virginia Tech Transportation Institute researchers to deploy smart work zone in Wise, Virginia,” Virginia Tech Exponentially 

More (May 19, 2022), https://vtx.vt.edu/articles/2022/05/vtt-smart-workzone.html?utm_source=cmpgn_news&utm_medium=email&utm_campaign=vtUnirelNewsDailyPublicCMP_052022-public; Audi, Audi 

collaborates to deploy C-V2X communication technology on Virginia roadways (Sept. 29, 2020), https://media.audiusa.com/en-us/releases/437. 

118 Press Release, Audi, (Mar. 30, 2021), Blue Bird, Fulton Co. Schools join Audi, Applied Information on connected 

vehicle deployment to boost school bus and school zone safety, https://media.audiusa.com/en-us/releases/465#

119 Press Release, Audi, Audi joins Spoke Safety, Qualcomm, Commsignia to help protect bicyclists through 

connected technology, https://media.audiusa.com/en-us/releases/514. 

120 https://www.its.dot.gov/pilots/pilots_thea.htm 121 https://teo.fdot.gov/architecture/architectures/d2/html/projects/projarch47.html
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automated, secure, and achieves four 9’s availability using dual concurrent 

cellular links.122 

• Tri-Met in Portland, OR. The Tri-County Metropolitan Transportation District of 

Oregon (TriMet) serves an area of 500 square miles, operating a fleet of over 700 

buses on 85 routes with thousands of stops. Smart systems maintain bus 

intervals and on congested corridors, prioritize bus travel over other vehicles by 

sensing bus arrival time then manipulating traffic signal phases123

• Positive Train Control- - SEPTA, LIRR, MNR, MBTA, AMTRAK. Positive Train 

Control (PTC) utilizes GPS, sensors and wireless communications technology to 

autonomously stop a train when necessary and to prevent train-to-train 

collisions, over-speed derailments, and unauthorized train movement. PTC 

helps ensures the safety of passengers by acting as a safeguard against human 

errors and other potential hazards.124

Generally speaking, these technologies include hardware, software, systems, and 

some type of connectivity. Hardware includes traffic signals and traffic controller 

assemblies, dynamic message signs, connected vehicle roadside units, cameras, 

sensors, LIDAR, electric vehicles (EVs) and EV charging equipment, vehicles with 

varying levels of autonomy (drones, delivery shuttles), and electric mobility (scooters, 

e-bikes). Systems include those that focus on security, intelligence, monitoring, and 

management. Software includes route planning and travel alerts. Connectivity 

includes- Cellular Vehicle to Everything (C-V2X), 5G, autonomous navigation both 

edge and cloud techniques. 

While there are several opportunities and benefits for personas that use these 

technologies, primarily in the realm of safety (e.g., emergency vehicle preemption, 

entering school or work zone, pedestrian crossing ahead), these technologies can also

provide valuable support functions such as package, food, and medicine delivery. 

There are also environmental benefits from congestion mitigation and providing an 

orderly flow of traffic (See Carnegie Mellon Study for an example: 

https://www.cmu.edu/piper/news/archives/2012/october/smart-signals.html) as well 

as increased productivity (drivers spend less time stuck in traffic). Other personas 

may use these technologies to develop and operate innovative transportation 

services, such as those involving multimodal transit, ridesharing, and autonomous 

transportation of people and goods. 

There also exist several barriers faced by personas seeking to implement these 

technologies. On the policy side clarity is needed with respect to data governance and 

122 https://www.digi.com/resources/customer-stories/new-york-city-dot-deploys-digi-solutions 123 https://www.digi.com/resources/customer-stories/trimet-bus-fleet-management-with-digi-connectivity 124 https://www.digi.com/resources/customer-stories/digi-helps-septa-comply-with-federal-mandate
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privacy and what aspects of data jurisdictions can collect, retain, and subsequently 

use. Certain aspects of this sector still need high level policies and regulations that 

adequately address safety and liability concerns. The benefits of these technologies 

are not available in rural or undeserved areas. Interoperability and fragmentation is 

also a challenge when dealing with different jurisdictions and it’s important to address 

cybersecurity implications of all the connected devices that can be used as a 

gateways. Finally, there is a considerable amount of funding needed to drive adoption 

in this sector. The examples provided above reinforce that this technology is ready to 

go mainstream.

Finding: Healthcare. IoT is transforming healthcare and is poised to 

revolutionize it, but significant challenges need to be addressed.

Supports Recommendation(s) x.x, x.x

The Internet of Things offers the potential to revolutionize healthcare by reshaping 

patient care, clinical workflows, and healthcare management. The integration of 

connected sensors, digital technologies, and data analytics creates a connected 

ecosystem of Internet of Medical Things (IoMT), medical devices, healthcare systems, 

and software applications that communicate with each other to streamline 

healthcare delivery, improve patient outcomes, and pave the way for a more efficient 

and patient-centric healthcare system.

IoMT devices range from wearable devices and remote patient monitoring solutions 

to smart medical implants. These IoMT devices encompass a vast network of smart, 

interconnected medical devices that collect, transmit, and analyze health data in realtime to enhance the quality of healthcare services and create a new era of 

personalized medicine. 

IoMT devices fall into four categories:

1. Wearable on-body devices, including consumer health devices (fitness 

watches, sleep trackers, etc.), and clinical-grade devices (regulated by health 

agencies, and prescribed by healthcare professionals). 

2. In-home devices that support telemedicine applications such as remote 

patient monitoring, and emergency response. 

3. Community IoMT systems, such as emergency response intelligence systems 

that connect patients and first responders, mobility services, and devices for 

measurement and regulation of temperature, blood pressure, etc.

4. In-clinic IoMT systems that support administrative functions that allow medical 

workers to help patients remotely, track hospital assets and equipment, etc. 
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Some examples of top IoMT applications include:

• Remote patient monitoring. One of the most impactful applications of IoT in 

healthcare is the continuous monitoring of patients outside traditional 

healthcare settings. Wearable devices track vital signs, medication adherence, 

and other health metrics. This allows healthcare providers to monitor patients 

outside traditional clinical settings, providing timely interventions and 

reducing the need for frequent hospital visits. This is beneficial for individuals 

with chronic conditions, allowing healthcare providers to remotely track and 

manage patients' health, reducing hospital readmissions, and enhancing 

overall patient well-being.

• Consumer health awareness. Wearable devices, such as smartwatches and 

fitness trackers, have become ubiquitous. These devices play a pivotal role in 

promoting preventive care, tracking physical activity, monitoring sleep 

patterns, and even detecting early signs of health issues, fostering a proactive 

approach to well-being.

• Enhanced patient care. IoMT has propelled the development of smart medical 

devices, including insulin pumps, pacemakers, and continuous glucose 

monitors. These devices not only offer real-time monitoring but also enable 

healthcare professionals to adjust treatment plans based on individual patient 

data, leading to more personalized and effective care.

• Asset and Inventory Management. IoT plays a crucial role in optimizing 

hospital operations by monitoring the location and status of medical 

equipment and supplies. This ensures that resources are efficiently utilized, 

reduces waste, and enhances overall operational efficiency.

IoMT enables the following benefits, including:

• Enhanced Patient Outcomes. By enabling continuous monitoring and 

personalized care, IoMT contributes to improved patient outcomes. Timely 

access to health data allows for early detection of potential issues, better 

management of chronic conditions, and more proactive interventions.

• Efficiency and Cost Savings. The implementation of IoT in healthcare 

streamlines workflows, reduces manual tasks, and enhances the efficiency of 

healthcare delivery. This not only improves the quality of care but also 

contributes to cost savings by minimizing unnecessary hospitalizations, 

optimizing resource utilization and minimizing administrative costs.

• Patient Engagement and Empowerment. IoMT empowers patients to actively 

participate in their healthcare journey. Access to real-time health data through 
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wearable devices fosters a sense of ownership and encourages individuals to 

make informed decisions about their lifestyles and treatment plans. 

While IoMT offers the potential to revolutionize healthcare, there are some challenges, 

including:

• Security and Privacy Concerns. The vast amount of sensitive health data 

transmitted through IoT devices raises significant concerns about data security 

and patient privacy. Ensuring robust cybersecurity measures and compliance 

with privacy regulations is crucial.

• Interoperability Issues. The integration of diverse IoT devices and platforms 

poses challenges related to interoperability. Standardization efforts are 

essential to enable seamless communication between different systems, 

ensuring a cohesive and efficient healthcare ecosystem.

• Regulatory Compliance. The rapid pace of IoT development often outpaces 

regulatory frameworks, leading to challenges in ensuring compliance with 

healthcare regulations. Addressing these issues requires ongoing collaboration 

between technology developers, healthcare providers, and regulatory bodies. 

The Internet of Medical Things holds immense promise for the healthcare industry, 

facilitating a future where patient care is personalized, efficient, and technologically 

advanced. However, to realize this promise, the healthcare industry ecosystem must 

evolve and adapt its practices, operations, policies and regulations. 

Finding: Environmental Sustainability. IoT supports environmental 

sustainability through real-time monitoring, optimizing resource usage, 

and facilitating data-driven decision-making across infrastructure and 

multiple sectors of the economy.

Supports Recommendation(s) x.x, x.x

IoT devices monitor environmental conditions, optimize usage of resources, and 

control operational processes. The data collected from IoT devices is analyzed and 

used to inform policymaking, enforce regulations and monitor progress and success 

of programs and initiatives. In other cases, IoT technologies initiate actions and control 

operational processes that support sustainability outcomes. 

IoT is used in a variety of applications to support environmental sustainability across 

all aspects of infrastructure and economy. Some examples of IoT applications for 

environmental sustainability include:
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• Monitor air quality. Air quality sensors measure the concentration of pollutants 

in the air, including particulate matter (e.g., soot or black carbon), and gas 

pollutants (carbon monoxide, nitrogen dioxide, etc.). This information informs 

residents of a community whether to go outside exercise or not. The collected 

data may be used by city and health officials to identify areas of poor air quality, 

and to devise programs to mitigate its effects (such as planting trees in the 

area, restricting traffic at certain hours, banning idling cars at certain hours, 

providing residents with respiratory healthcare information, etc.).

• Optimize water use. Farming consumes a lot of water. Soil moisture sensors, 

integrated with automatic irrigation systems, measure moisture levels and 

activate the irrigation systems in those spots in the field where the water is 

needed. This helps save water (and the corresponding expenses) by precisely 

directing water to those spots where it is needed. This optimizes water usage 

by applying water it is most needed and reducing waste and conserving 

resources.

• Reduce carbon emissions. Intelligent traffic management systems, 

incorporating IoT sensors, detect heavy traffic conditions and automatically 

adjust traffic signals to reduce congestion. This increases the capacity of the 

street or freeway to handle more cars, while reducing the time cars are idling. 

The overall effect is a reduction in emissions and its impact on residents of the 

surrounding community.

• Reduce energy use. Buildings are one of the largest consumers of electricity. 

Room occupancy sensors turn off lights in empty rooms. Smart thermostats 

learn the behavior of building occupants and autonomously manage ambient 

temperatures based on those patterns. Automated demand response systems, 

connected to building automation and energy management systems, 

automatically reduce energy use by turning things off during peak demand 

periods while minimizing impact on building occupants.

• Optimize use of renewable energy sources. IoT optimizes and maximizes the 

use of renewable energy sources to power communities and cities. Smart 

inverters in solar power systems and sensors in batteries communicate with 

the local electrical grid to continuously manage how much electricity is stored, 

discharged to the grid, and used to power loads in the home and business. This 

maximizes the ability of renewable energy systems to meet demand in the local 

grid, while delaying the use of upstream fossil fuel power generation plants to 

meet local community demand.
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The use of IoT to support environmental sustainability offers the following benefits, 

including:

• Improved and more effective outcomes. The use of IoT enables the direct 

monitoring of the environment at the precise locations needed. The data 

collected can be used to improve and validate simulation models, and to 

predict likely trends and patterns. This foresight leads to more informed policies 

and strategies, which can then be implemented and monitored. 

• Increased resource use efficiency. Analysis of the collected data provides 

insights that lead to optimization strategies. For example, a study of energy 

usage data helps identify patterns that may be adjusted. Automation systems 

may be programmed with these insights to optimize energy utilization, 

minimizing waste and enhancing efficiency.

• Agile and proactive response. Real-time monitoring of environmental 

conditions, such as water contamination and air quality levels, allow the 

community to plan and respond swiftly. This enhances the effectiveness of the 

response, the number of resources applied, and minimizes the extent of the 

adverse impacts. 

• Informed and data-driven decision making. The vast amount of data 

collected by IoT devices enables informed decision-making for policymakers, 

businesses, and individuals in the pursuit of sustainability goals. This leads to 

more effective policies and strategies, more productive use of resources, and 

sustainable outcomes.

The use of IoT for environmental sustainability faces a number of challenges. These 

include:

• Data accuracy. Environmental monitoring is performed by many types of 

sensors. For example, air quality sensors range from low-cost sensors 

“consumer grade” to expensive regulatory grade units. Despite measuring the 

same things, these sensors have different accuracy levels due to the underlying 

sensing technologies used. Low-cost sensors would not be suitable for use in 

situations where environmental monitoring is used for verification of 

compliance. In addition, sensors experience calibration issues, drift, or 

malfunctions, leading to inaccurate readings. 

• Lack of supporting infrastructure. Environmental monitoring devices may be 

deployed in remote or rural areas with limited or unreliable network 

connectivity, affecting the real-time transmission of data. For example, many 

wildfires start in remote areas and early detection is critical to containing the 
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impact. Many river monitoring stations are located upstream in remote areas. 

Ocean monitoring buoys are located in areas with no infrastructure. These 

remote areas have limited to no connectivity service, and hinders the ability to 

deploy IoT in these areas.

• Initial Implementation Costs. The upfront high costs of purchasing and 

deploying environmental monitoring sensors are a barrier for many agencies 

and communities. These costs are increased if a large network of sensors is 

needed. For example, in a city environment, air quality levels significantly. A 

street next to a freeway has poorer air quality than a street a mile away. In those 

applications where a dense network of sensors is needed, such as community 

air quality monitoring, the costs can beyond the financial means of the 

purchasing agency.

• Data management. Environmental monitoring sensors collect a large volume 

of data over time. During a storm, sensors monitoring rising river water levels 

during a storm collect data more frequently than when it is not raining. 

Managing this data is complex and challenging. This is complicated when 

sensor data from different brands is combined. These sensors have different 

accuracy levels, different measurement methods, and different methods for 

how the readings are calculated. Normalizing the data is laborious and timeconsuming. This data must then be stored and maintained. The challenge is 

magnified as the volume of data collected grows.

• Interoperability. Environmental monitoring is a fragmented ecosystem of 

diverse devices and sensors, each designed with specific communication 

protocols and standards. This lack of standardization hinders seamless 

integration and data exchange between different IoT platforms and devices, 

limiting the holistic view required for comprehensive environmental 

monitoring. The lack of standardized communication protocols hinders the 

ability of environmental monitoring networks to expand and scale. Without 

standardized interfaces, scaling up becomes a cumbersome task, leading to 

increased complexity in managing and maintaining diverse systems. The 

challenge is further exacerbated pronounced when attempting to create a 

unified system that aggregates data from various sources, such as air quality 

sensors, water quality monitors, and weather stations. Overcoming 

interoperability challenges is crucial for establishing a cohesive and 

interconnected network of environmental monitoring devices, enabling more 

accurate and comprehensive assessments of environmental conditions.
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Finding: Public Safety. IoT can enhance and improve public safety outcomes, but 

must overcome a wide variety of technical, community and policy challenges, 

before it can be deployed and used at scale.

The Internet of Things offers the potential to increase public safety by enhancing the 

capabilities of public health systems, emergency response systems, law enforcement, 

and disaster management. The incorporation and integration of connected sensors, 

digital technologies and data analytics creates applications that improves monitoring 

and detection, response effectiveness, and recovery and resilience actions. Some 

examples of IoT applications for public safety include:

• Smart Surveillance. IoT-enabled surveillance cameras and sensors are 

deployed in public spaces to monitor and detect unusual activities or potential 

threats in real-time. For example, connected audio sensors detect the sound of 

gunshots or breaking glass, identify the location and notify police so they can 

respond faster. Smart cameras detect and report suspicious and unpermitted 

behaviors, such as unattended luggage or packages, trespassing into secure 

areas, lack of social distancing, or fighting, display of a gun and other illegal 

activities. These smart applications enable and accurate monitoring and review 

of thousands of camera and sensor feeds autonomously with limited human 

involvement. In addition, when integrated with next-gen 911 systems, IoT 

systems provide dispatchers and first responders with relevant information and 

situational awareness for more effective deployment of resources and 

personnel. 

• Situational Awareness. The use of IoT provides communities and responders 

with detailed information about existing and future events. For example, 

drones fly over active disaster areas to provide responders with a fast 

assessment of the scene to inform on deployment of resources and activities. 

Water level sensors monitor upstream river and stream levels to provide 

communities with knowledge of real-time conditions and enhance flood 

response, evacuation, and mitigation activities. Sensors that detect Wi-Fi

signals from mobile phones allow first responders to know how many people 

are inside a building and where they are at. Air quality sensors monitor the 

pollution levels of communities, and inform public health officials of 

intervention programs to mitigate respiratory illnesses. The use of IoT for 

situation awareness facilitates where to focus initial resources to save human 

lives.

• Responder Monitoring. Wearable IoT devices, such as body cameras, biometric 

monitors, and communication devices, enhance the capabilities and safety of 

first responders during operations. These IoT devices inform operations 
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managers of responder stress levels, conditions of the surrounding 

environment and state of responder equipment. For example, sensors on 

oxygen tanks provide responders with a real-time estimate of the remaining 

time left, and takes into account responder exertion and stress levels. Body 

cameras on police provide a record of how officers respond to activities, 

document actions, hold officers accountable and provide a record of activities 

that is reviewed to improve future operations. 

• Connected patient monitoring. Emergency response vehicles equipped with 

IoT devices monitor the health of the people being treated at accident or 

disaster scenes, as well as those critically injured transported by ambulances. 

This monitored patient information can be viewed in real time by Emergency 

Room doctors, who may instruct paramedics to apply additional measures to 

stabilize and treat patients before they reach the hospital. For the most critically 

injured, the additional information could mean the difference between life and 

death.

The use of IoT to support public safety activities offers the following benefits, including:

• Improved Situational Awareness. IoT devices provide real-time data, 

supplementing existing information. and enabling public safety agencies, first 

responders, disaster and resilience managers, and health officials to have a 

comprehensive and real time view of ongoing and developing situations. This 

improves decision-making and facilitates resource allocation during 

emergencies.

• Increased Response Effectiveness. Connected devices enable faster 

communication and response coordination. Emergency services can be 

dispatched more efficiently, reducing the time it takes to address critical 

situations.

• Preventive and Predictive Capabilities. IoT sensors enable the collection of 

data for predictive analytics. For example, information collected from gunshot 

detection sensors can be analyzed to predict when and where potential future 

incidents may occur. The police can anticipate potential risks and take 

preventive measures like stationing more officers at the predicted times and 

locations, to reduce the likelihood of incidents.

• Data-Driven Decision-Making. The data collected from IoT complements 

existing and historical information and knowledge to inform and enhance 

decision-making. For example, air quality monitors identify areas of a city where 

poor air quality consistently exists. Using this knowledge, along with the 
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correlation between increased death rates and air pollution,125 public health 

officials can decide to target this area for information campaigns to prevent 

COVID-19 exposure, as well as to station medical resources for early intervention 

and treatment of COVID related illnesses. 

The use of IoT to support public safety actions faces a number of challenges, including:

• Cybersecurity Concerns. The use of connected devices leads to increased 

cybersecurity vulnerabilities and risks. Cybercriminals may use vulnerable 

devices to gain unauthorized entry into the systems used by law enforcement 

and other public agencies. This may result in access of sensitive information, 

and the operational compromise of public safety devices and systems. 

• Privacy Issues. The extensive data collection capabilities of IoT devices raise 

privacy concerns. For example, traffic cameras may be used outside of its 

original and authorized scope to surveil private citizens. Cameras in public 

spaces may be equipped with facial recognition capabilities to identify people 

for detention. These concerns may lead to a lack of community support and 

ban of these technologies in the communities they serve. The use of IoT 

requires the development of policies and legislation that balance the benefits 

of data-driven public safety with individual privacy considerations.

• Interoperability Challenges. The IoT devices used to support public safety may 

face interoperability challenges in integrating and communicating with the 

various systems used by public safety agencies. This lack of interoperability 

makes it difficult for the various systems to share and process information in 

real time for operations, decision-making and situational awareness. 

• Scalability and Infrastructure. Scaling IoT deployments to cover large 

geographic areas requires robust and modern infrastructure. This 

infrastructure must be scalable and interoperable to accommodate a growing 

number of future devices, and be reliable and critical for use under harsh 

conditions. It must cover remote areas, such as for wildfire detection or flood 

monitoring, where limited connectivity infrastructure currently exists. 

• Funding. A lack of funding prevents public safety and public health agencies 

from procuring, deploying and operating IoT-enabled applications and 

systems. These systems may be costly, and limit agencies to what they can 

purchase. Traditional funding sources have been through a variety of agency 

125 Air pollution linked with higher COVID-19 death rates, https://www.hsph.harvard.edu/news/hsph-in-the-news/airpollution-linked-with-higher-covid-19-death-rates/
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funding vehicles, including grants, internal capital budgets, and capital 

improvement budgets. Other than grants, funding is based on agency priorities 

and availability, and can be subject to long procurement cycles.
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Recommendations of the IoT Advisory Board

As the IoT Advisory Board (IoTAB) met repeatedly throughout the year, several topics 

and eventually themes surfaced repeatedly across the IoT landscape. The board’s 

recommendations are organized around five major themes. These themes represent

elements that are fundamental to facilitate, accelerate and sustain the adoption and 

integration of IoT into the American economy and society. These themes are:

1. Establishing a National IoT Strategy and Leadership 

2. Modernizing IoT Infrastructure

3. Establishing Trust in IoT

4. Incentivizing the IoT Economy including a Resilient IoT Supply Chain

5. Facilitating Adoption

6. Fostering a IoT-ready Workforce 

The IoTAB recommends that the IoTFWG consider (and where appropriate, act to 

implement or document the existing implementation of) the findings and 

recommendations in this report. The Board remains in place until [date] to clarify any 

points for the IoTFWG or to answer any questions about these recommendations.
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Recommendations Summary

[Ed. Note: When the recommendations are mostly stable, we will place a table here as 

a quick reference, with hyperlinks to each recommendation.] 
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Establishing a National IoT Strategy and Leadership

Objective 1: Congress and the White House must work together to create and 

implement a coherent comprehensive coordinated national IoT strategy, as 

numerous federal experts have suggested over the years.

Key Recommendation KR1.1: The IoTAB recommends a strategic national

approach for taking full advantage of the opportunity presented by the IoT. 

Supported by Finding x.x

The United States is undergoing a profound transformation - one that is driven by 

economic, societal, and cultural innovations brought about by the Internet of Things 

(IoT). This fourth industrial revolution intertwines connectivity and digital innovation 

with the opportunity to drive a revolutionary metamorphosis across all parts of our 

nation. By integrating the physical with the digital to interconnect devices, systems 

and people, we envision an Internet of Things that will enable a more resilient nation, 

supercharge economic growth, increase public safety, create a more sustainable 

planet, individualize healthcare, and facilitate an equitable quality of life and wellbeing. This progress will be best facilitated by a strategic national approach for IoT. 

In 2010, the President’s Council of Advisors on Science and Technology (PCAST) 

recommended the Federal Government invest in a national, long-term, multi-agency, 

multi-faceted research initiative in these areas.126 They said, “those agencies tackling 

problems whose solutions entail instrumenting the physical world ... should conduct 

research to design, fabricate, and test sensors that are problem-domain specific and 

that are cheaper, smaller, better packaged, lower powered, and more autonomous 

than those available today.” 

In 2011, an OSTP/NSTC White Paper outlined many reasons why we needed a more 

comprehensive and strategic approach for taking advantage of the Cyber Physical 

System (IoT) opportunities over the horizon to grow our economy and help solve our 

national challenges.127 They found that “Isolated efforts by mission agencies are 

simply not sufficient to address the underlying issues in a holistic manner.” Trying to 

address such issues agency-by-agency or sector-by-sector would result in 

inefficiencies and insufficient progress relative to system development timetables, 

and we might never get to where we need to be, and the recommended the creation 

of a long-range action plan. 

126 The 2010 PCAST report is available from: https://www.nitrd.gov/pubs/PCAST-NITRD-report-2010.pdf 127 The OSTP/NSTC white paper is available from: https://www.nitrd.gov/pubs/CPS-OSTP-Response-Winning-TheFuture.pdf
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They went on to say, “Without a strong, central focus on innovation and the common 

issues in translational research for innovation in cyber-physical systems, including 

standardization, manufacture, and deployment, each of the jump start activities 

above runs the risk of devolving into an isolated, marginally-effective effort.”

Likewise, a NITRD Report from 2012 that looked at opportunity in Agriculture, smart 

building, defense, emergency response, energy healthcare, manufacturing and 

transportation, advocated for a multi-agency, multi-sector comprehensive focus on 

the difficult crosscutting R&D challenges in CPS.128

As shown in the earlier section The Current State of IoT, these predictions from 2011 

and 2012 were accurate, and the lack of a national strategy has impacted growth. And 

today the IoT opportunities are even more pervasive, the economic stakes even more 

enormous, and the impacts are even more profound. In other words, it is not too late.

We need a comprehensive national IoT strategy that: 

• describes a comprehensive vision for the federal government’s role in IoT;

• articulates the role that IOT can play across sectors and agencies, and within 

sectors, in advancing national priorities and solving social challenges – across 

health, transportation, manufacturing, energy etc.; 

• ensures continued U.S. leadership in connected device technologies, a vibrant 

and innovative commercial sector, and U.S. leadership in the way the 

technologies are harnessed to address national challenges; 

• comprehensively catalogues the game changing work the administration is 

already doing across many agencies in fundamental research, development, 

demonstration and deployments – and the important role agencies are playing 

in meeting our critical needs;

• identifies potential opportunities, and synergies across agencies, and identifies 

remaining gaps; and, 

• outlines an R&D roadmap around the often multi-disciplinary R&D needs to 

push new frontiers and achieve major grand challenges. 

Like nano.gov, ai.gov, and the Chips for America websites, stakeholders will benefit 

from central Internet presence that will share the strategy and vision, demonstrate 

the many ways the government is tackling these issues, and engage stakeholders in 

meaningful ways. By monitoring and tracking progress of various initiatives, federal 

128 The 2012 NITRD report is available from: 

https://www.nitrd.gov/nitrdgroups/images/6/6a/Cyber_Physical_Systems_%28CPS%29_Vision_Statement.pdf
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leaders will be able to track achievement of key outcomes of the IoT strategic 

approach. 

Enabling Recommendation ER1.1.1: IoT must be added back to the critical 

and emerging technology list. 

Supported by Finding x.x

The U.S. National Standards Strategy focuses on emerging technologies, yet the IoT is 

no longer included in the list of critical emerging technologies 

https://www.whitehouse.gov/wp-content/uploads/2022/02/02-2022-Critical-andEmerging-Technologies-List-Update.pdf. This is a problem since IoT is critical to U.S. 

prosperity and socioeconomic success and still faces many barriers to adoption. IoT 

must be added back to the CET to ensure that the government remains aware of new 

opportunities to apply IoT and ensure adequate oversight. 

In addition, IoT is an evolving set of disparate technologies at various levels of maturity. 

While some are mainstream and mature, others are emerging and immature. 

Source: https://iot-analytics.com/iot-technologies/ 

Technologies such as cloud computing, IoT platforms, containers, supervised machine 

learning, IoT streaming analytics, cellular IoT and Low Power Wide Area Networks 
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(LPWAN) have reached maturity.129 Others are “coming up”, including edge data and 

app platforms, serverless/Function-as-a-Service, cloud-connected sensors, edge AI 

chips, and low code/no code development platforms and satellite IoT connectivity.130

Still others like data ecosystems, automated machine learning, wireless battery-free 

sensors, neurosynaptic chips, QRNG chips, biodegradable sensors, 6G and quantum 

computing are still “years out” and require continued research investments.131

Enabling Recommendation ER1.1.2: Congress should further improve and 

elevate inter-agency coordination. 

Supported by Finding x.x

Within the White House, the National Science and Technology Council (NSTC)

conducts research coordination across the federal government. For more than a 

decade, there was a Cyber-Physical System (CPS) Inter-Agency Working Group, which 

has made some important contributions and recommendations to advance IoT fields. 

But in 2019, its focus was diluted. It is important to ensure there is an NSTC IoT 

committee that is properly named, elevated, and empowered, just like other NSTC 

committees focused on AI, Quantum and Nanotechnology. This is particularly 

important as formerly separate disciplines of AI, Quantum and IoT begin to converge. 

It’s also critical that an approach must be inclusive of IoT and the many different 

names and enablers. 

The U.S. should lead in the adoption and integration of emerging technologies like 

the IoT into the U.S. economy and infrastructure. Currently a lack of coordination from 

the Executive Office of the President leads to siloed planning, policies, execution, 

suboptimal utilization of resources, duplicate programs, monitoring, thus limiting 

realization of economic, social, security and other values and benefits. 

Congress should expand the mission of OSTP for additional focus on the IoT as 

identified by the National Standards Strategy of May 2023 or similar curated list, with 

additional staffing support as required for the expanded mission. OSTP has historically 

played a critical role in coordinating such inter-agency endeavors.

Congress should create and fund a new National Coordination Office for IoT/CPS for 

advancing this strategy, like it has in the areas of Nanotechnology, Quantum, and AI. 

129 “55+ emerging IoT technologies you should have on your radar (2022 update),” S. Sinha, IoT Analytics, April 6, 2022. 

Link

130 ibid.

131 ibid.
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In doing so, it should also ensure that OSTP is fully resourced and funded to be able 

to take on these tasks – or risk losing focus on other critical needs.

Enabling Recommendation ER1.1.3: The government should fully fund 

existing IoT research, development, deployment and demonstrations.

Supported by Finding x.x

We recommend Congress complete the funding procedure for vital IoT related R&D 

and deployment work already approved and taking place throughout the federal 

government. That means appropriations that fully fund the critical investments that 

a bipartisan Congress has supported through the bipartisan Chips and Science Act, 

and through the bipartisan Infrastructure Act, and that these be fully funded at the 

levels Congress authorized. These research investments span multiple areas, 

including semiconductors and sensors, to the connectivity and interoperability 

methods that connect them, to the infrastructure and systems that allows them to 

operate, automate and sustain itself at scale.

In addition, the U.S. Government should fully fund science agencies that are doing 

work in these areas through important IoT-related programs such as those at ARPA, 

DOE, NSF, and DOT. It may also require a more significant role for OSTP in IoT-related 

research. Failure to do so will slow down government efforts and cut our IoT 

opportunity short.

Enabling Recommendation ER1.1.4: The government should consider 

upgrading legacy federal owned or operated buildings that have 

inadequate security in their connected systems. 

Supported by Finding x.x

By upgrading these buildings, they can set an example for private industry to follow. 

They could then promote conversion in other market segments such as industrial 

factories or power plants. Credibility and assurance can also be provided to the private 

sector when the Federal Government leads by example.

Many government buildings are reliant on building control systems which provide the 

functional, operational, and safety needs of a building. These can serve as gateways 

for malicious actors who can take control of critical applications (including life and 

safety-related services) within a building (i.e., heating, air conditioning, physical 

access). 
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While such upgrades may be costly, it is possible that some of those costs could be 

offset by reduced cybersecurity insurance premiums and other fiscal benefits. 

It is also notable that a great deal of data in an unprotected building control system 

may contain significant amounts of personal and confidential information.

Implementation considerations: The Environmental Protection Agency (EPA) has a 

program for Energy Star Building Certifications and there could be a similar program 

that addresses cybersecurity within a building. There are some efforts already 

underway within the commercial real estate sector that could be leveraged 

(https://buildingcybersecurity.org/). There are also parallels that could be explored 

such as the National Cyber Labeling Program for Consumer IoT versus Energy Star on 

appliances. 

Implementation could occur through updated acquisition requirements, such as in 

the GSA Federal Acquisition Regulation (FAR) and Defense Federal Acquisition 

Regulation (DFAR). 

Owners of buildings used by federal organizations should, at a minimum, use basic 

cyber hygiene best practices (i.e., changing default passwords, segmentation of 

networks by using items such as firewalls, installing patches) as directed within 

requirements. NEMA has developed a cyber hygiene best practice document for end 

users that is available at the following URL 

(https://www.nema.org/standards/view/cyber-hygiene-best-practices-part-2) 

Enabling Recommendation ER1.1.5: The government should specify and 

use, for federally-funded projects, IoT technologies and applications that 

are energy efficient, sustainable, and “smart”. 

Supported by Finding x.x

The federal government, through its procurement and funding activities, can 

influence and facilitate action to improve IoT adoption. For example, the GSA and the 

U.S. Army Corps of Engineers specified the use of Building Information Modeling (BIM) 

in its projects. As a result, contractors had to comply with the requirement and used 

BIM tools, which enabled both the government and the contractor to reduce 

construction and project risks. A similar approach was used to accelerate the 

utilization of small and disadvantaged businesses (SB and SB8a) in federally funded 

transportation projects. Use of IoT in federal projects also bolsters trust in the reliability 

and trustworthiness of the technology.
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In 2021, the Administration set ambitious 2030 greenhouse gas emissions goals.132 By 

requiring increased use of energy efficient technologies, the U.S. can make progress 

toward these and other environmental goals. IoT tools and technologies play a central 

role in managing energy efficiency.

Specific examples include smart thermostats that can regulate room temperature 

data, intelligent lighting systems that are enabled to be turned on and off as needed, 

and smarter buildings that use IoT sensors to send data on energy consumption 

allowing it to be analyzed further so the building can more efficiently manage its air 

conditioning, water, heating, or lighting. Implementation might include adoption of 

building and energy codes that include language like automated demand response 

technologies, EV Ready, EV Capable, etc. Also look at incorporating energy savings 

through energy performance contracts and examination of building energy use 

benchmarking. The GSA FAR specifies energy efficiency requirements for 

procurement in federal owned and operated buildings.

The federal government should consider the specification and utilization of IoT and 

“smart” technologies into infrastructure and other projects that are funded in full, or 

partially, with federal funding. Every year, the federal government, through its many 

agencies, supports and funds billions of dollars of infrastructure planning, 

construction and operation projects. These projects include projects owned by nonfederal stakeholders (municipalities, utilities, agencies, states, etc.) and federal 

stakeholders (federal facilities, infrastructure, etc.).

The government should also take this opportunity to specify and incorporate IoT and 

smart technologies into infrastructure projects spanning the project lifecycle from 

design, construction, to commissioning and operation. For example, IoT technologies 

can be specified and used during the construction phase of infrastructure projects. Air 

quality sensors can be specified to monitor vehicle emissions and dust and particulate 

matter generated during construction in order to comply with local air quality 

regulations. When air quality levels reach certain levels, mitigation measures can be 

implemented to minimize impacts to worker and community health. IoT sensors and 

intelligent traffic solutions can be specified into roadway projects to support future 

intelligent highway and automated vehicle projects. Remodeling or construction of 

new federal facilities, including airports, military bases and buildings can specify the 

use of various IoT solutions, such as smart building sensors and energy management 

systems, smart parking, and other technologies.

132 https://www.whitehouse.gov/briefing-room/statements-releases/2021/04/22/fact-sheet-president-biden-sets-2030-

greenhouse-gas-pollution-reduction-target-aimed-at-creating-good-paying-union-jobs-and-securing-u-sleadership-on-clean-energy-technologies/
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Enabling Recommendation ER1.1.6: The federal government should 

continue to support and fund technology research, through industry, 

university and its national labs, to further advance and accelerate the 

development of IoT technologies and its enabling infrastructure. 

Supported by Finding x.x

The federal government should continue to support and fund technology research, 

through industry, university and its national labs, to further advance and accelerate 

the development of IoT technologies and its enabling infrastructure. Doing so will 

enable the United States to build the technical infrastructure that will support the full 

realization of the outcomes provided by IoT. 

Some example areas of research that are important to the further development of IoT 

include (but not limited to):

• Enabling more capable and intelligent devices. Processing of IoT workloads 

is increasingly moving to the edge to support requirements for low latency, 

high reliability and autonomous operations. Advancements in increasing 

device processing capabilities to support AI workloads, decreasing processor 

energy consumption, and low-cost sensors and processors are needed.

• Enabling network infrastructure to support IoT at scale. Network and 

communications infrastructure must support billions of heterogeneous IoT 

devices, distributed across the cloud, edge and mobile environments. 

Advancements in a number of areas, such as the management and operations 

of distributed networks, spectrum sharing and management, infrastructure to 

support AI and complex IoT application workloads, fault tolerant and resilient 

infrastructure, and context-aware computing are needed.

• Enabling usable AI for IoT. The convergence of AI and IoT promises to unlock 

the value of the data and the autonomous capabilities enabled by the Internet 

of Things. Advancements such as development of AI algorithms that can 

operate on resource constrained devices, ethical AI, explainable AI tools, 

collective intelligence (including swarms) and ambient IoT systems.

• Enabling human-centric usable IoT. The full value of IoT is realized when it is

embedded and integrated transparently into all aspects of our economy, 

society and lives. Facilitating the realization of beneficial outcomes requires 

that IoT be human centric and usable. Advancements in a number of areas, 

such as the design of IoT systems for human-AI interaction and collaboration, 

development of trust in human-AI interactions, and user experience and user 

interactions. 

• Enabling trustworthy IoT. Trust in IoT is paramount in a hyperconnected 

future with billions of IoT devices integrated into all aspects of the economy. 
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Current research and industry efforts, centered around cybersecurity and 

privacy, should continue. Additional research is needed to drive advancements 

in the development of trustworthy IoT systems in a wide variety of areas. 

Examples include confidential computing, lightweight quantum-safe 

cryptographic algorithms for resource constrained devices, and software 

defined networking and self-defending adaptive networks. 

• Enabling interoperability. The ability for devices and systems to freely 

exchange data and communicate is a key enabler in fully integrating and 

scaling IoT into the economy. Continued research and development of various 

standards, frameworks, and protocols is essential. 

The internet of things is continually evolving in response to a variety of adopter needs. 

Continuing research and development is needed to create the technological 

advancements needed to meet these needs and remove the barriers hindering its 

adoption. For example, the shifting of data processing from the cloud to the edge 

supports the need for low latency and autonomous operations. However, processing 

on the device and on edge servers add significant complexity to the design, operation 

and management of these systems and applications. New technologies must be 

developed to build the innovations necessary.

Industry efforts are focused on the development of nearer term innovations. These 

efforts typically support incremental improvements and nearer term goals. Federal 

research investments catalyze the development and acceleration of new innovations 

that have broad impact to the economy and transferred to industry, as well as those 

that industry may not necessarily focus on, and those that are high risk with uncertain 

outcomes. 

Small Business Leadership

Key Recommendation KR1.2: The government should accelerate IoT 

technology adoption as well as manufacturing for small businesses and 

startup organizations. This can be done via policies, procedures, and 

funding methods that specifically target them.

Supported by Finding x.x

The federal government should accelerate IoT technology adoption and 

manufacturing for small business and startup organizations. This can be done via 

policies, procedures, and funding methods that specifically target them. Small 

businesses and startup organizations who are looking to adopt or manufacture IoT 

technologies may find it challenging to know where to start or have the resources and 
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knowledge to do so. Federal funding mechanisms and procurements targeted to 

them can aid these companies by giving them a resource to help speed and 

incentivize their adoption. 

Enabling Recommendation ER1.2.1: The government should accelerate the 

adoption of IoT technologies manufactured by small business and startup 

organizations through targeted Federal Government programs, policies, 

procedures, and funding methods.

Supported by Finding x.x

The federal government should accelerate the adoption of IoT technologies 

manufacturers by small business and startup organizations. This can be done via 

policies, procedures, and funding methods that specifically target them. It is 

particularly challenging for small businesses and startup companies in this sector that 

have to provide upfront capital and full understanding in successfully navigating 

opportunities both within the federal government and with federal government 

support to market externally. The process for these projects can also take many years 

to bring them from proposal to commercial operation and these companies may not 

have patient resources.

Small businesses have the primary option of using a channel with existing 

relationships to cities to make sales which is also unpredictable and not very scalable. 

This makes it challenging for small businesses and startups. Federal funding 

mechanisms and procurements targeted to them can aid these companies so they 

can more effectively compete with larger organizations on RFPs relevant to their 

business. There are many existing Federal Government programs and policies that 

support small businesses and startup organizations. Rather than create from scratch, 

this recommendation advises tapping into these existing programs and have a 

dedicated IoT technologies track for related small businesses and startups in this 

space. 

Implementation Considerations: The Federal Government could set aside readily 

tappable funding pools year-round for innovation and next-generation technologies. 

Grants could also be set aside for categories that the government deems high 

importance. The Federal Government could fast-track programs for startups and 

small companies to deploy this technology in pilots. There should be consideration to 

set up a system to make it easier for startups and small companies to find relevant 

funding sources like grants and SBIR awards. The Federal Government should 

encourage local governments to leverage its local startup accelerator network to 

develop technology and fast-track it to local adoption on successes. 
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The Federal Government can modify guidelines for grant programs and funding 

mechanisms already in existence for small businesses to allow for greater 

incorporation of IoT technologies, examples include:

• The U.S. Department of Commerce, Minority Business Development Agency (MBDA) 

(https://www.mbda.gov/who-we-are/overview) 

• DOE Office of Small and Disadvantaged Business (https://www.energy.gov/osdbu/officesmall-and-disadvantaged-business-utilization) 

• National Science Foundation Program for Small Business 

(https://www.nsf.gov/funding/smallbusiness.jsp) 

Enabling Recommendation ER1.2.2: The government should accelerate the 

adoption of IoT technologies manufactured by small business and startup 

organizations. 

Supported by Finding x.x

This can be done via policies, procedures, and funding methods that specifically target 

them. 

The federal government should accelerate the adoption of IoT technologies 

manufactured by small business and startup organizations. This can be done via 

policies, procedures, and funding methods that specifically target them. It is 

particularly challenging for these types of manufacturers in this sector that have to 

provide upfront capital, access, and knowhow, before hopefully being selected as a 

result of an RFP. The process for these projects can also take many years to bring them 

from proposal to commercial operation and these companies may lose both funding, 

ability, and interest in that time frame.

Small businesses IoT technology manufacturers have the primary option of using a 

channel with existing relationships to local governments to make sales which is also 

unpredictable and not very scalable. Federal funding mechanisms and procurements 

targeted to them can aid these companies so they can more effectively compete with 

larger organizations on RFPs relevant to their business. 

Greater adoption of IoT technologies manufactured by small businesses and startups 

could help in the following examples: 

• Incorporation of technologies enabled by IoT: Opportunities for IoT 

technologies are manufacturers by small business and startups across the IoT. 

For example, in smart, connected transportation these technologies include 

sensors, cameras, and edge computing devices that can improve safety in 

things such as vulnerable road users (i.e., pedestrians at crosswalks), traffic 
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intersections, school, and work zones. Opportunities for IoT technologies in 

electrified transportation manufactured by small businesses and startups 

include in car systems or mobile apps that can locate charging stations, as well 

sensors that manage charging stations to gather data about usage and 

performance, to anticipate maintenance needs, and troubleshoot problems. 

• Greater competition across IoT markets: Incentivizing small businesses and 

startups to bid on projects and deploy their technology will increase their 

market penetration and provide end-users more technology options. This 

would lead to greater competition in selected markets providing end-users the 

ability to select manufacturers based on several factors such as cost, quality of 

products manufactured, service, and innovation. 

Implementation considerations:

• The Federal Government should set aside fast-track programs for startups and 

small companies to deploy this technology in pilots.

• The Federal Government should set up a system to make it easier for startups 

and small companies to find relevant funding sources like grants and SBIR 

awards and RFP opportunities.

• The Federal Government should encourage local governments to leverage its 

local startup accelerator network to develop technology and fast-track it to 

local adoption on successes. 

• The Federal Government can work with the national chamber of commerce, 

rotary clubs, small business associations, start-up accelerators/incubators, state 

partnership programs to help identify relevant IoT manufacturers to support 

and get input on the programs. 

• The Federal Government can modify guidelines for grant programs and 

funding mechanisms already in existence for small businesses to allow for 

greater incorporation of IoT technologies. Examples include the following:

o The U.S. Department of Commerce, Minority Business Development Agency 

(MBDA) (https://www.mbda.gov/who-we-are/overview) 

o DOE Office of Small and Disadvantaged Business 

(https://www.energy.gov/osdbu/office-small-and-disadvantaged-businessutilization) 

o National Science Foundation Program for Small Business 

(https://www.nsf.gov/funding/smallbusiness.jsp) 
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International Leadership

Key Recommendation KR1.3: The government should promote 

international collaboration in IoT adoption across global supply chains to 

share knowledge, best practices, and resources. 

Supported by Finding x.x

Promoting international collaboration in the drive to adopt IoT technologies presents 

a unique opportunity to foster the sharing of knowledge, best practices, and resources 

among countries and regions. The goal is to spur innovation and accelerate the 

widespread adoption of IoT technologies. Stakeholders like the United States Federal 

Government, European Union Commission, and Asian Development Bank can form a 

global ecosystem that supports the development and deployment of IoT solutions, 

thereby tackling challenges related to interoperability, standardization, and 

regulatory compliance.

This international collaboration necessitates the creation of platforms and forums that 

allow policymakers, industry stakeholders, technology providers, and researchers 

from different countries to come together. Such platforms could include international 

bodies like the World Economic Forum, United Nations Industrial Development 

Organization, and International Telecommunication Union. These stakeholders can 

engage in a productive exchange of ideas, address common challenges, and explore 

opportunities for joint projects and initiatives. The outcome of these collaborations 

could be the development of harmonized regulations, standards, and guidelines that 

enable seamless integration of IoT systems across borders. This harmonization can 

foster efficient and resilient global supply chain networks. 

International collaboration can facilitate the pooling of resources and expertise to 

support research and development efforts, pilot projects, and capacity-building 

initiatives aimed at promoting IoT adoption, such as in supply chain management. 

Organizations like the World Bank and World Trade Organization can help bridge the 

digital divide between developed and developing countries, ensuring that businesses 

worldwide have access to the tools and technologies needed to harness the potential 

of IoT in their operations. This collective effort, led by governments actively engaging 

with international partners and participating in relevant forums and organizations, 

can contribute to the development of a connected and resilient global supply chain 

ecosystem that benefits businesses and consumers alike.
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Enabling Recommendation ER1.3.1: The government should create 

internationally compatible data minimization guidance related to IoT 

devices, aligning with the NIST Privacy Framework and NIST Cybersecurity 

Framework principles.

Supported by Finding x.x

Data minimization processes (related to both collection and retention of sensitive 

data) reduce potential harm from data breaches or unauthorized access. Data 

minimization is inherently supportive of Privacy By Design. Implementation of these 

processes, and reduced risk that would result, may boost consumer trust by ensuring 

data is only used for necessary purposes. Consistent processes (supported by 

international agreement) would also help establish uniform data privacy standards 

globally.

The government should collaborate with public sector, private sector, and 

international counterparts to develop universally acceptable guidance on data 

minimization that would be tailored to various IoT applications.

Those working to foster international agreement on data minimization should 

recognize that the resulting processes should not hinder innovation or 

competitiveness in the IoT industry. This will be a delicate balance that may require a 

long-term commitment to advocacy since international agreements often require 

considerable time and negotiation. Principles of this guidance would be considered

in future international agreements. 
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Modernizing IoT Infrastructure

Objective 2: The U.S. should call upon and collaborate with industry to enhance and 

modernize the infrastructure that enables and supports IoT. Such collaboration 

should include the provision of clear direction and support for data sharing methods 

and repositories, consistent and resilient ways for interoperable communications

among devices, update of legacy computing and networking systems, and improved 

means to connect among devices and interconnect with existing technologies.

There are four critical aspects to modernizing and expanding this infrastructure: 

• Data Sharing,

• Consistent and Resilient Interoperability and,

• Updating of legacy computing and networking systems 

• Enhanced Connectivity.

The U.S. Government should call for immediate attention to these needs, as it has 

done for other topics through strategic objectives and planning. In particular, NIST 

may be able to support the development of outcome-based objectives that inform 

industry consensus standards and may be able to offer assistance as industry 

collaborates and develops those standards. That partnership may also help support 

international success in expanding and improving IoT infrastructure and reliability.

Equitable and Responsible Data Sharing

Key Recommendation KR2.1: The government should foster policies that 

encourage responsible and equitable sharing of IoT data and thereby drive 

economic growth, societal benefits, and sustainability. 

Supported by Finding x.x

Data policies can have a major impact on privacy, security, innovation, and 

monetization. Importantly, the lack of data policies can create uncertainty and hinder 

the growth of digital economies. Identifying opportunities to monetize data further 

enables business growth and can fuel synergistic ecosystems.

The federal government can apply policies to facilitate data protection, sharing, 

licensing, and analytics can minimize risk and maximize economic value.

Specifically, agencies should consider the potential impact of data policies and 

provide guidelines for data use and monetization. Society will benefit from the 

promotion of interoperability for data sharing, and from improved collaboration and 

information sharing among agencies and industry.
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Implementation considerations: Implementation of this recommendation would 

include programs to promote the necessary infrastructure for data security and 

privacy, including aspects of data sharing, licensing, ownership, analytics, control, and 

monetization. Agencies would need to establish and maintain data policies that 

ensure compliance with regulatory requirements, in consultation with industry, 

academia, and government agencies. 

Enabling Recommendation ER2.1.1: The government should establish 

templates or best practices for clear and robust corporate policies 

regarding data sharing, usage, and licensing among parties in the IoT 

ecosystem. 

Supported by Finding x.x

Where practical, agencies can help foster voluntary, industry-led adoption of such 

policies to enhance transparency, reliability, and consistency in applying IoT. These 

types of best practices are vital due to the significant data protection risks presented 

by IoT’s increased interconnectivity and data-sharing capabilities. The government 

should establish templates for non-sensitive data collected by federal IoT systems 

(e.g., air quality, water monitoring). Since these risks may discourage IoT adoption, 

clear corporate policies safeguarding users' personal data and ensuring transparency 

would foster trust and expanded IoT use. 

Implementation considerations: The government should create guidelines on 

effectively communicating data sharing and data use in relevant corporate policies, 

in alignment with other recommendations from this report. Those guidelines and 

policies would be supported by public awareness campaigns to educate users about 

their expectations for the use of data and to share information about how to properly 

share and protect IoT data. 

Enabling Recommendation ER2.1.2: The government should partner with 

industry and collaborate with international allies to develop and support 

comprehensive data sharing policies that stimulate economic growth, 

societal benefits, and sustainability.

Supported by Finding x.x

As the growth of IoT continues to drive the growth of data availability, policies will be 

needed regarding data confidentiality, ownership, control, management, access, 

licensing, and trust for data use in applications, to minimize security risks and 

maximize economic value.
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Monetization of data will require infrastructure for security, privacy, data sharing, 

ownership plus control frameworks for identity and access management (IAM), data 

protection, sharing and exchange, data analytics and AI, to minimize supply chain risk 

and maximize economic value. Policies related to data can have a major impact as 

they can fuel synergistic ecosystems and the future digital economies.

A lack of clear and consistent data policies can create uncertainty and hinder the 

growth of digital economies. The right data strategy can drive business growth and 

fuel synergistic ecosystems. Policy guidance from the government will support the 

infrastructure required for data sharing (i.e., for security, control, trust, licensing, 

identity & access management (IAM), and analytics), and will also help support 

consistent protections, such as anonymization of collected data (an essential element 

of privacy, safety initiatives, and other risk management considerations).

Implementation Considerations: The government should work with industry to help 

establish model policies related to trusted data, including identification of areas that 

are critical or sensitive enough that regulatory oversight might be necessary. That 

process can include methods for promoting essential requirements and guidelines 

(such as for data privacy, confidentiality, and anonymization) and define methods for 

how stakeholders (e.g., industry, academia, civil society, and government agencies) 

might evolve the policies to keep them up to date with changing technologies and 

business models.

As the government works with partners to create policies that promote 

interoperability and data sharing across different systems and corporations, the 

resulting efficiency may be particularly helpful for SMBs.

Enabling Recommendation ER2.1.3: The government should establish data 

repositories for privately collected data.

Supported by Finding x.x

Note: there seems to be considerable dislike for this recommendation. Please be 

prepared to discuss one more time at our meeting. 

The growth of the Internet is directly traceable to the fact that large amounts of data 

can be efficiently and responsibly stored, enabling significant exploration to gain 

insights into a myriad of information types. For more than a decade, the U.S. 

Government has recognized that data is a key asset that can provide valuable benefits 

to its citizens and other stakeholders. As with many existing datasets, there is an 

opportunity for the Government to help create and maintain repositories for IoT data, 

ensuring transparency and availability. 
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The growth in IoT devices portends a rapid deployment of devices. IoT devices 

generate large amounts of data, some of which is likely to include information that 

may be openly shared with a broad constituency, as many thousands of existing open 

datasets do. There is value in helping to establish private data stores that can be 

licensed for particular consumer segments, bringing value to those who operate 

some types of IoT devices (accelerating adoption) and supporting availability of 

important information to those who would consume the information produced.

Federal data repositories provide transparency and the opportunity to empower 

community research to conduct analysis on the data far beyond the capabilities of a 

single federal agency. The government should support and facilitate industry efforts 

to create these data repositories for the purpose of collecting public data such as a 

common societal good like weather or environmental data (e.g., air quality, water level, 

etc.). In this way, the government can use non-sensitive federal open data as a basis 

for the community research and analysis to determine the right level of deployment 

for IoT devices. These devices have the potential to provide a strong public good, 

however without transparency, privacy and data ownership issues may arise.

Additionally, the use of different technologies and methodologies across different 

platforms may result in conflicting measurements, fostering misinterpretation and 

reducing public confidence in the monitoring process.

Implementation Considerations: There are existing examples where the federal 

government has provided a clearinghouse for raw data and other information. For 

example, the Department of Energy’s EIA sharing of power plant data may provide a 

template and lessons learned for similar sharing.

Consistent and Resilient Interoperability

Key Recommendation KR2.2: The government should establish methods to 

foster interoperability for IoT technology, including through the use of 

consistent models, protocols, application interfaces, and schemas.

Supported by Finding x.x

While the Internet of Things and related technologies have made significant 

advancements in recent years, much of that work has been focused on the devices 

themselves with less focus on the interoperability, compatibility, and connectivity that 

converts these discrete “things” into an “Internet of Things”. In some cases, while 

manufacturers have provided reliable interoperability within their own product line, 

improved interaction among a broad range of devices from disparate producers will 
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encourage competition and technology availability, thereby increasing adoption by 

enterprises and consumers. 

There exist many standards today and there may be a better method for determining 

which standards should be used under specific conditions. In some cases, formal 

standards may be needed, such as those from a standards development organization 

or from a technical engineering organization (e.g., Institute of Electrical and 

Electronics Engineers (IEEE)). It is likely that wholly new standards and models will not 

need to be created “from scratch” but rather, industry collaboration is likely to advance 

existing communications and interoperability protocols that can rapidly be 

encouraged and adopted. The Board did not identify any single protocol that will solve 

the interoperability issues, since these models tend to application or domain specific. 

Therefore, the Board highly recommends not to mandate any formal or informal 

standard or protocol, but rather to encourage voluntary conformance in the interest 

of improved interoperability.

A model of industry-led interoperability in another space—not IoT, but streaming

media—is the WAVE Project hosted by the Consumer Technology Association. This 

program has participation from major streaming media services, major smart TV and 

device hardware manufacturers, and other necessary ecosystem entities. The goal is 

to foster interoperability between the streaming media and the hardware playback—

that is, from one’s favorite video streamer to one’s smart TV, media stick or set-top box. 

The WAVE Project convenes most of the major players in these categories. The subject 

matter experts from each company work not to make new standards, but to ensure 

consistent application of existing accepted industry standards. By constraining the 

many options in the standards to a few and creating test suites to test for conformance 

to those constraints, the WAVE Project helps all of these organizations’ products to 

“speak the same language”. [ref. https://CTA.tech/WAVE] 

A common theme from IoT users through the development of this report was their 

concerns about getting “locked-in” to a particular vendor’s proprietary technology. 

These concerns currently act as an impediment to IoT adoption.. No company or 

agency wants to invest in infrastructure that will rapidly become obsolete. Quite the 

opposite is true – in many cases, IoT infrastructure may need to operate for many 

decades. Parallel examples such as Wi-Fi (supported through IEEE 802 series 

technical standards) and cellular industry consortium standards demonstrate that 

interoperability and standardization do not reduce a vendor’s ability to innovate. Quite 

the opposite seems to be true – the ability for products to work together has great 

possibilities for both established manufacturers and newcomers. 

Before the government can foster specific standards, it may be helpful for one or more 

agencies to perform a survey of available and relevant standards, protocols, and 
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models. Due to the differences in sub-sectors, each such effort must be constrained 

to a specific application space, such as smart home or IoMT. Such a survey would be 

helpful, for example, if agencies wish to include open standards and consortium 

developed standards as part of the requirements for federal funded projects. Federal 

recommendations (or requirements) for a taxonomy or set of applicable models will 

promote industry adoption and foster standardization. 

Enabling Recommendation ER2.2.1: The government should work with 

various organizations to facilitate interoperability through the 

development of a consistent data taxonomy for the sharing and exchange 

of data collected from IoT and non-IoT sources. 

Supported by Finding x.x

As an example, transportation and traffic agencies have a limited ability to share and 

exchange data. Transportation data includes things like geographic information, asset 

and infrastructure information, traffic mobility history, public transportation 

performance, and traffic anomalies. At best, these exchanges may happen on a 

limited basis within each agency, but not across other agencies in other jurisdictions. 

This makes collaboration requiring multiple agencies difficult.

Once a taxonomy is established, government and industry can partner to develop 

conformance review criteria and methodology, further facilitating the reliable and 

consistent exchange of information.

Implementation considerations: Projects involving multiple jurisdictions and 

requiring federal funding should specify the development of a data taxonomy that 

can be further used and developed by other jurisdictions. It’s also important to engage 

with appropriate industry associations.

Enabling Recommendation ER2.2.2: The government should support 

research and industry-led standards in areas such as telematics and sensor 

technologies for automated vehicles. 

Supported by Finding x.x

These standards should be based on high-level safety guidelines (perhaps as 

determined by the National Highway Traffic Safety Administration or another federal 

organization).

The automated vehicle market is still emerging. AVs exist in states like California and 

Arizona, however in other areas of the country they are only found in designated geo-
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fenced areas like a university campus. It will be some time before these exist on 

current highways / streets that have vehicles with human drivers. Research is needed 

to determine how AVs will interact with these vehicles, with roadside infrastructure, 

and with pedestrians. In addition, research is needed to show how these interactions 

change in times of bad weather. 

Adoption of vehicle-related standards would promote improved safety and reliability 

through better vehicle and infrastructure communications and interoperability. 

Consistent communications standards will promote innovation as vendors work (and 

compete) to develop products and services that will work together. This increased 

production and adoption is expected to drive cost savings, further advancing 

adoption and benefits.

High-level safety guidelines will need to be finalized by the National Highway Traffic 

Safety Administration as there are still open liability questions particularly regarding 

a determination of fault in the event of an accident. Spurred by these guidelines, 

industry can develop appropriate performance and safety standards in a market that 

is still emerging while avoiding the possibility of market fragmentation. It’s important 

that all key stakeholders in the automated vehicle ecosystem participate in these 

safety discussions and standards development activities. 

The existing UNECE regulatory framework for automotive security133 is not a U.S. 

regulatory requirement, but it is in force in over 50 countries, making the 

cybersecurity requirements of WP.29 a de facto global standard. Since automakers 

already conform to these regulatory requirements in other areas, significant 

consideration should be given to avoid unnecessary overlap or redundancy. 

Enabling Recommendation ER2.2.3: The government should promote and 

adopt industry led standards, guidelines, and protocols for minimum 

baseline interoperability for smart transportation technologies and 

corresponding transportation infrastructure (i.e., sensors in roads, cameras 

at intersections).

Supported by Finding x.x

Industry standards and protocols ensure that devices from different manufacturers 

can communicate and work together seamlessly. In particular, smart transportation 

systems focus on safety, so standardization (especially for security and interoperability 

needs) is vital to ensuring that devices can communicate basic safety information to 

133 https://unece.org/wp29-introduction
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other vehicles and to/from infrastructure. There are also cases where baseline 

standards, guidelines and protocols can address existing market fragmentation 

scenarios particularly in the global market. 

Standards and protocols can set a path forward for subsequent government 

regulations or policies and are particularly relevant if industry led standards are 

attempting to address known gaps and market fragmentation issues. This is 

particularly important when dealing with multiple states and local jurisdictions. 

Standards can stimulate innovation and competition by providing a level playing field 

for businesses and developers as well, regardless of their size or market share. With a 

level baseline achieved via a multi-stakeholder process, companies can now build 

upon it and tailor their own solutions. Standardization can lead to cost savings for 

businesses by reducing the need for customized solutions and simplifying the 

procurement process. 

Promoting Existing Methods 

Key Recommendation KR2.3: The government should promote 

collaborative development across industries to adopt existing industry 

standards and protocols.

Supported by Finding x.x

It is likely that wholly new standards and models will not need to be created “from 

scratch” but rather, industry collaboration is likely to advance existing 

communications and interoperability protocols that can rapidly be encouraged and 

adopted. The Board did not identify any single protocol that will solve the 

interoperability issues, since these models tend to application or domain specific. 

Therefore, the Board highly recommends not to mandate any formal or informal 

standard or protocol, but rather to encourage voluntary conformance in the interest 

of improved interoperability.

The federal government should consider interoperability to address the many 

technologies, some of which are proprietary technologies and the consideration for 

scalability over time. There needs to be innovation and competition, a way to save on 

costs through simplified procurement, a foundation for future policies through 

mechanisms of regulatory compliance, and the means to facilitate market entry. 
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Enabling Recommendation ER2.3.1: The government should advocate for 

the implementation and adoption of interoperable data standards for 

public safety IoT. 

The proliferation of IoT devices without interoperable data will make it difficult to 

achieve interoperability the longer it diverges. In public safety, the interoperability of 

IoT device data will enhance incident responses and coordination among responder 

teams, providing safety benefits that would encourage the adoption of IoT. Solutions 

might include facilitation of adoption by funding grants for jurisdictions/agencies for 

procurement of interoperable IoT solutions. Support could also include development 

of education/training materials to help jurisdictions/agencies apply best practices for 

interoperability.

Implementation considerations: Compiling guidelines and best practices for entities 

from what currently exists as a starting point (e.g., NISTIR 8255: Interoperability RealTime Public Safety Data, CISA SAFECOM Interoperability Continuum, etc.), prioritizing 

solutions which adhere to interoperability guidelines in government contracts for 

public safety IoT (e.g., bulk purchase pricing a la General Services Administration (GSA) 

catalog). From a high level, the consideration of tax incentives that would encourage 

companies to implement public safety IoT with interoperable data standards and the 

education and promotion of interoperable data guidelines for public safety IoT across 

different jurisdictions (e.g., local and regional).

Enabling Recommendation ER2.3.2: The government should promote and, 

if necessary, develop a protocol for data exchange standards for IoMT 

(Internet of Medical Things) for interoperability, and promote the adoption 

of these standards.

Supported by Finding x.x

Data exchange standards for IoMT would result in data interoperability, which would 

result in efficiencies and provide safety benefits that would encourage the adoption 

of IoT. This standardization would support coordination among relevant stakeholders, 

including product manufacturers and healthcare organizations, to ensure widespread 

adoption. 

Implementation considerations: As data exchange standards for IoMT are developed 

and refined, agencies could prioritize the (in federal procurements and government 

contracts) solutions which adhere to or implement those solutions. Simply promoting 

the benefits (e.g., improved interoperability, potential cost reductions, avoiding 

vendor lock-in) to the community and education for healthcare organizations could 
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increase adoption. The federal government could also incentivize (e.g., through tax 

incentives) companies to implement the IoMT data exchange standard. 

Enabling Recommendation ER2.3.3: The government should promote the 

development and use of standards for supply chain logistics, traceability, 

and assurance. 

Supported by Finding x.x

The federal government should foster the development, adoption, and use of 

standards and protocols for supply chain logistics, traceability, and assurance. It 

should collaborate with Standards Development Organizations (SDOs) and 

international allies to promote assured & traceable products by manufacturers for 

efficient, reliable, and secure supply of goods. It should incentivize suppliers to 

establish unique corporate IDs, product IDs, asset IDs, and part IDs linked to a digital 

thread of information and data, that are used to track and trace goods while 

improving supply chain efficiency, transparency, resilience, and security. (See Key 

Recommendation 4.2 for more on digital threads.) There is value in encouraging the 

use of Global Identifier Standards (such as GLS of GS1) in procurement contracts and 

regulatory frameworks and track goods and info related to assets and data, to 

optimize risk, cost, benefits, and value. 

The federal government should offer financial and technical support to businesses, 

particularly small and medium-sized enterprises, to help them adopt and comply with 

the established standards and protocols. There should be mechanisms to monitor and 

evaluate the effectiveness of the standards and protocols over time and adjust as 

needed to address emerging challenges and opportunities. Additionally, the federal 

government should also support industry-led initiatives and education campaigns to 

foster the development and adoption of IoT standards and protocols for supply chain 

management, traceability, and enablement of economic value. These standards 

should best enable interoperability, reliability, and security across IoT-enhanced 

supply chains, facilitating data exchange, decision-making and services. By creating 

and promoting such standards, the government can drive widespread adoption of IoT 

technology, minimize supply chain risk, and maximize economic value to businesses 

and users.

Implementation Considerations: Encourage inclusiveness from a diverse range of 

stakeholders. Prioritize critical areas of supply chain management where 

standardization can yield significant benefits (i.e., data exchange, device 

interoperability, security, and privacy). Build on existing standards as a starting point 

and adapt/expand as necessary and identify where gaps exist to create new 

standards. Design standards and protocols that can accommodate new technologies, 
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emerging threats, and evolving industry needs. Promote adoption to incentivize 

businesses. Develop mechanisms to monitor and enforce compliance to standards. 

Foster global collaboration to incentivize suppliers. Promote use of unique identifiers 

across the supply chain. Facilitate the adoption of identifiers through incentives, 

education, and outreach programs and promote linking Identifiers to IoT 

cybersecurity labeling programs for different markets. Create incentives to upgrade 

existing supply chain management systems to include global identifier standards that 

ensure seamless tracking and tracing. 

Enabling Recommendation ER2.3.4: The government should promote 

standards and protocols for IoT technology in supply chain management 

to provide assurance of interoperability, reliability, and security across 

various IoT systems and devices.

Supported by Finding x.x

Doing so would foster innovation and competition among all parts of the supply chain, 

simplify integration and maintenance for supply chain partners, examine the 

cybersecurity and privacy risks, scalability over time, provide cost savings, and 

potentially meet regulatory compliance.

By establishing a set of common standards and protocols, businesses can seamlessly 

integrate IoT solutions into their existing supply chain operations, facilitating data 

exchange, and enabling more efficient and informed decision-making processes.

Developing industry standards and protocols involves collaboration between 

government agencies, industry stakeholders, technology providers, and researchers 

to identify the key specifications for IoT systems in supply chain management. This 

may include addressing issues such as data formats, communication protocols, 

interoperability APIs, security measures, and device compatibility, among others.

In addition, the government should promote the adoption of these standards and 

protocols through education and awareness campaigns, providing businesses with 

the necessary resources and guidance to successfully implement IoT solutions in their 

supply chain operations. By creating industry standards and protocols, the 

government can help to create a stable and unified foundation for IoT technology, 

driving its widespread adoption, and maximizing its potential benefits for businesses 

and consumers alike.

Implementation considerations: The range of stakeholders should be considered 

from diverse persona groups including businesses, technology providers, academia, 

government agencies. There should be a prioritization on critical areas first (e.g., 
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exchanging data, device interoperability, security). There should be a focus on 

building on existing standards ahead of creation of new ones.

Connectivity

Key Recommendation KR2.4: The federal government should expand and 

improve programs that ensure sufficient availability, reliablility and 

connectivity for IoT in all areas of the country. 

Supported by Finding x.x

By definition, IoT technology must be able to internetwork through some physical, ad 

hoc/mesh, or wireless capability. While communications technologies (e.g., satellite, 

cellular, broadband/Wi-Fi, and other traditional licensed communications 

technologies) have expanded in both geographic scope and capacity to 

accommodate higher data loads in recent years, the capabilities are not unlimited. 

This condition is exacerbated by the fact that, in many cases, the very places where 

some IoT sensors are needed, such as for remote security and environmental 

monitoring, are locations with limited connectivity. Scalability represents another IoT 

challenge: the communications infrastructure must simultaneously support 

hundreds of billions of digital conversations.

The government should further promote accelerated innovation to ensure improved 

communications by ensuring the availability of suitable and sufficient spectrum 

resources, the development of wide-area networking technologies, and enhancing 

interoperability. The rapid evolution of communications technology in recent history 

demonstrates the significant promise and opportunity for the nation to improve IoT 

connectivity. Current capabilities that were science fiction in the past are now routine 

in our daily lives. The U.S. must continue such advances to ensure that IoT can securely 

and reliably communicate and interoperate wherever devices are applied. 

Additionally, enabling recommendations found elsewhere in this report that support 

sector specific examples of connectivity include: 

• Under Agriculture – 

o 5.4.5: The government should facilitate development of connectivity 

policies and programs. 

• Under Environmental Monitoring – 

o 5.11.3: The government should facilitate the expansion of wireless 

connectivity to support remote monitoring and sensing in areas not 

serviced by traditional connectivity.
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Enabling Recommendation ER2.4.1: To promote continued U.S. leadership 

on spectrum policy, the government should continue to make licensed and 

unlicensed spectrum available via spectrum sharing, repurposing

underutilized federal spectrum and spectrum auctions. 

Supported by Finding x.x

The government, through collaboration between the National Telecommunications 

and Information Administration (NTIA) and the Federal Communications Commission 

(FCC) has successfully identified a significant amount of under-utilized federal 

spectrum that could be made available for private sector use, including for IoT 

applications. This policy should be continued and should continue to support both 

licensed and unlicensed applications. 

As has been noted, IoT applications are expanding and continued growth is 

expected.134 The technology industry uses both licensed and unlicensed spectrum to 

enable this growth. Spectrum availability should not become a choke point in this 

growth.

A component of the government’s toolkit for enhancing spectrum availability is the 

sharing of existing spectrum among stakeholders, “spectrum sharing”. The FCC has 

enabled several models of dynamic spectrum sharing. This is a helpful tool when 

utilizing spectrum whether existing private sector bands, or underutilized federal 

spectrum.

Repurposing under-utilized federal spectrum is also an ongoing and important effort. 

However, there is an obstacle in repurposing spectrum to 6G.

Since 1993, the FCC has had authority to auction spectrum through competitive 

bidding, unlocking thousands of megahertz of spectrum and powering each new 

generation of wireless technology.

In 2023, Congress allowed the FCC’s auction authority to lapse. Without this authority, 

a major tool in the U.S. government’s toolkit for enhancing IoT connectivity through 

spectrum access is lost: FCC authority to open up spectrum for commercial purposes 

via auction.

By restoring the FCC’s auction authority, Congress can get the agency back to making 

additional spectrum available for commercial use, including for IoT applications. 

Additional spectrum will power future generations of wireless connectivity including 

134 Op cit the prior background discussion on billions of IoT devices in coming years.
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6G. This capability will be important for mobile-connected IoT devices and 

applications such as precision agriculture. 

Unlicensed spectrum is also widely used in connected devices and needs its own 

priority. To see the vast range of unlicensed spectrum applications, refer to 

https://shop.cta.tech/collections/research/products/unlicensed-spectrum-and-theus-economy-quantifying-the-market-size-and-diversity-of-unlicensed-devices.

Enabling Recommendation ER2.4.2: The government should increase 

funding and accelerate implementation of broadband deployment across 

rural America.

Supported by Finding x.x

A recent U.S. Department of Agriculture (USDA) report identified that 60% of U.S. 

farmland doesn’t have good internet connectivity. While innovative solutions have 

expanded in recent years, point to point solutions and satellite-based connectivity 

quickly become expensive and do not resolve all issues. For example, it can be difficult 

to maintain connectivity to all areas of a farm. 

The federal government currently offers limited funding and grants (e.g., Department 

of Agriculture – Community Connect Grant Program) to help fund broadband 

deployment in rural communities, however, these opportunities have not advanced 

quickly enough to provide broadband coverage for certain areas of rural America. 

Implementation considerations: The U.S. should aggressively promote broadband 

infrastructure deployment across rural areas until U.S. coverage is complete. Current 

federal funding operates across several programs making it difficult to identify and 

find the opportunities available to specific areas. 

In some cases, network communications equipment could be installed if power 

sources were adequately available. For this reason, funding might include options for 

supplying energy sources such as solar power, wind power, or micro-hydro power 

where access to reliable electricity is limited.

Other connectivity solutions that federal agencies could explore include taking 

advantage of modern communications technology and protocols, such as 5G mobile 

broadband, fixed wireless systems, and low-earth orbit (LEO) satellites.
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Enabling Recommendation ER2.4.3: The government should actively 

promote and support the adoption of satellite narrowband IoT systems, 

with the aim of improving connectivity, data collection, and decisionmaking in rural and remote areas, resulting in economic growth. 

Supported by Finding x.x

Satellite IoT systems provide a reliable and efficient means of connectivity and data 

transfer in remote agricultural areas where traditional terrestrial connectivity options 

may be limited or unavailable. Encouraging the adoption of satellite IoT systems will 

enable farmers to optimize their operations through real-time data management, 

resulting in benefits for various stakeholders, including farmers, policymakers, 

agricultural companies, and consumers. 

Encouraging the adoption of satellite IoT systems will enable adopters such as 

farmers, those monitoring infrastructure (e.g., powerlines, river levels), or rural remote 

patient monitoring to optimize their operations through real-time data management, 

resulting in benefits for various stakeholders, including farmers, policymakers, 

agricultural companies, utility companies, medical personnel, and consumers. 

Reliable and consistent support for such remote connectivity requires harmonization 

of standards for satellite narrowband IoT. The Board recommends that satellite 

narrowband solutions be explored and developed for specific applications such as 

agricultural applications and environmental monitoring needs. 

Implementation Considerations: 

Establish a public-private-academia partnership: This partnership should involve 

satellite service providers, IoT technology companies, Agriculture data-platform 

providers, Ag Extension Centers, research institutions, and relevant government 

agencies. The goal of this partnership would be to support the development, 

implementation, and adoption of satellite IoT systems in agriculture. 

Define specific agricultural applications: Consider specific use cases for satellite IoT in 

agriculture, such as precision farming, crop monitoring, water management, livestock 

tracking, and supply chain traceability. Tailor solutions to address these specific needs 

to maximize the impact of satellite IoT technology in the agricultural sector. 

Develop financial incentives and subsidies: Provide incentives or subsidies to facilitate 

the adoption and integration of satellite IoT systems by farmers and agricultural 

businesses. These incentives could include tax breaks, grants, or low-interest loans to 

help offset the upfront costs associated with implementing satellite IoT systems. 
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Promote education and training: Create educational programs and resources to help 

farmers and agricultural professionals understand the benefits of satellite IoT 

technology and how to effectively implement and use these systems. This can be 

achieved through collaborations with Ag Extension Centers, universities, and industry 

experts.

The role of states should be clearly defined, and funding for satellite IoT infrastructure 

and adoption may be allocated to states to manage and distribute. Incentives or 

subsidies for satellite IoT adoption and integration could be considered as part of the 

upcoming Farm Bill or other relevant legislation. There might be international 

coordination, along with spectrum considerations with the International 

Telecommunications Union (ITU).
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Establish Trust in IoT 

Objective 3: The U.S. has an opportunity to build more trust and confidence in IoT. 

IoT provides powerful benefits but reaping those benefits, at times, requires 

placing sensors and devices in physical locations that can be highly sensitive and 

intrusive. While IoT promises exciting innovation and advancement 

opportunities, trust in the technology (and in the protection of associated data) 

by industrial adopters and other stakeholders is a key prerequisite. Trust 

considerations directly influence IoT adoption, including IoT safety, reliability, 

and ability to protect sensitive information stored and processed.

Cybersecurity Improvement

Key Recommendation KR3.1: The Federal Government should provide 

specific and consistent cybersecurity guidance for IoT providers and 

adopters to ensure secure operations in a whole-of-government approach.

Supported by Finding x.x

While not the exclusive source of cybersecurity guidance, NIST should continue to be 

recognized as a developer of outcome-based requirements that inform industry 

consensus standards, and industry as the developer of those standards.

Until now, NIST’s role has been to develop recommended baselines and outcomes for 

the entire IoT ecosystem. Industry subject-matter experts have participated in 

developing requirements for their specific sectors that align with NIST criteria. NIST’s 

overall cybersecurity expertise is well-known, as is that of the sector-specific experts. 

By tasking NIST with developing required outcomes, and industry with specific 

requirements to meet those outcomes, each side works in an area of strength. These 

roles are working and should continue.

Enabling Recommendation ER3.1.1: The government should strengthen 

cybersecurity measures focused on IoT across supply chain networks to 

address concerns around data privacy, security, confidentiality, trust, and 

potential risks associated with increased connectivity and 

interdependence of IoT systems. 

Supported by Finding x.x

The recommendation to strengthen cybersecurity measures focused on IoT across 

supply chain networks aims to address the growing concerns around data privacy, 

security, and the potential risks associated with the increased connectivity and 
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interdependence of IoT systems. While many manufacturers have adopted best 

practices, many more have not. By implementing robust cybersecurity measures, the 

government can help ensure that businesses can confidently adopt IoT technologies 

in their supply chain operations without compromising the security and integrity of 

their networks and data. 

Strengthening cybersecurity measures involves promoting the development and 

adoption of security best practices, guidelines, and standards specifically tailored to 

IoT systems in supply chain management. This includes securing data transmission, 

storage, and access, as well as protecting IoT devices and networks from unauthorized 

access, manipulation, and cyberattacks. 

To implement this recommendation, the government should collaborate with 

industry stakeholders, cybersecurity experts, and technology providers to identify 

potential vulnerabilities and develop appropriate solutions that address the unique 

security challenges associated with IoT systems in supply chain operations. For 

example, the emerging U.S Cyber Trust Mark program is proving to be a model of 

public-private cooperation, Administration leadership and agency execution.

Additionally, the government should support research and development efforts 

aimed at advancing cybersecurity technologies and solutions tailored for IoT 

environments.

Training and awareness programs should also be promoted to ensure that businesses 

and professionals understand the importance of IoT security and are equipped with 

the knowledge and skills required to protect their systems and data. By strengthening 

cybersecurity measures focused on IoT across supply chain networks, the government 

can foster trust in IoT technologies and enable businesses to fully leverage their 

potential benefits while minimizing risks.

Enabling Recommendation ER3.1.2: The government should consider 

additional ways to highlight those vulnerabilities most likely to be 

applicable to IoT product developers.

Supported by Finding x.x

Provide guidance to IoT developers to help them efficiently meet requirements in 

standards or best practices for addressing “critical vulnerabilities” (or similar 

requirements for making sure known or identified vulnerabilities are addressed). This 

may be accomplished, for example, by providing a list of known IoT operating system 

vulnerabilities that developers should be aware of and address, or a means to filter an 

existing list for such vulnerabilities.
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The government provides key guidance to the private sector in many categories. For 

IoT, CISA has guidance for IoT acquisition (https://www.cisa.gov/resourcestools/resources/internet-things-iot-acquisition-guidance-document), use 

(https://www.cisa.gov/news-events/news/securing-internet-things-iot), and for specific sectors 

(https://www.cisa.gov/sites/default/files/publications/CISA%20IoT%20White%20Paper_3.6.19%

20-%20FINAL.pdf).

The government also maintains vulnerability lists, including the National Vulnerability 

Database (NVD) maintained by NIST (https://nvd.nist.gov/vuln/Vulnerability-Detail-Pages) 

and the Known Exploited Vulnerabilities Catalog (KEV Catalog) maintained by CISA 

(https://www.cisa.gov/known-exploited-vulnerabilities-catalog). 

An IoT developer is encouraged or required to make sure they address any “known 

vulnerabilities” or “critical vulnerabilities” as part of best practices. The FCC NPRM on 

the U.S. Cyber Trust Mark program (FCC 23-65 in PS docket no. 23-239) mentions 

“identified security vulnerabilities” @58 and “critical patches” @40. 

One can already filter by “IoT” as a keyword in the National Vulnerability Database, 

which pulls up 1100+ hits. Those results include many product-specific hits. For 

example, CVE-2023-23575 is, “Improper access control vulnerability in CONPROSYS 

IoT Gateway products allows a remote authenticated attacker to bypass...” That 

information is useful to users of the CONPROSYS product, but not to IoT 

developers. But buried in that the same set of results are items relevant to IoT 

developers. For example, CVE-2023-23609 is, “Contiki-NG is an open-source, crossplatform operating system for Next-Generation IoT devices. Versions prior to and 

including 4.8 are vulnerable to an out-of-bounds write...” As Contiki is an IoT operating 

system, this result would potentially be useful in this context. 

While there is a national interest in IoT developers addressing critical vulnerabilities, 

there appears to be no resource in the public or private sector that can be mapped to 

IoT vulnerabilities. 

Enabling Recommendation ER3.1.3: The government should accelerate the 

promotion and adoption of procedures and methods to make the electric 

grid enabled by IoT more reliable and resilient.

Supported by Finding x.x

A more reliable and resilient grid can better accommodate the integration of 

renewable energy sources enabled by IoT. This is made possible through the 

incorporation of technologies enabled by IoT (i.e., smart inverters, energy storage 

systems) resulting in quicker restoration from natural and man-made threats, more 
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efficient transmission of electricity, and potential cost reductions both for utilities and 

consumers.

Implementation Considerations: DOE Funding. Near-term technologies provide 

short-term solutions at a lower cost (e.g., Dynamic Line Ratings, Volt/Var, Power-Flow 

Controllers, Energy Storage, Distributed Energy Resources, and Demand Response). 

Microgrids that operate and function as a grid resource.

Enabling Recommendation ER3.1.4: Congress and regulatory agencies 

should support domestic IoT cybersecurity labeling initiatives by 

establishing incentives for manufacturers to participate. 

Supported by Finding x.x

Participation in the U.S. cybersecurity label program has begun strong, but with the 

expectation that certain issues would be addressed over time. Manufacturers cite 

concerns over perceived new liabilities incurred by adding the label to the product, as 

well as concerns over the existing possibility of enforcement action by relevant 

agencies in the event of a device hack. Relief from this concern could be via an earned 

safe harbor provision and agencies’ affirmation that participants in the program have 

met a criterion of “reasonable security”. 

Other incentives include preemption of mismatched state regulations for program 

participants, global recognition of the U.S. mark, and well-funded government 

campaigns to educate consumers about the mark. 

Implementation considerations: 

• Congress should enact an “earned safe harbor” that includes protection for 

program participants from civil actions. 

• Regulatory agencies should act within the scope of their authority to clarify that 

earning the U.S. Cyber Trust Mark meets their expectations of reasonable 

security or the equivalent. 

• Congress should establish preemption of mismatched state laws for program 

participants. 

• The Department of State, the FCC and NIST should negotiate mutual 

recognition or “equivalence” across borders. 

• Congress should ensure adequate funding for a robust consumer education 

campaign. 
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Enabling Recommendation ER3.1.5: Congress must ensure adequate and 

continuing funding for the Cyber Trust Mark consumer education 

campaign.

Supported by Finding x.x

The U.S. Cyber Trust Mark program can empower consumers to make informed

decisions about the cybersecurity of the connected products they purchase. This in

turn can move the market, providing manufacturers with an incentive to improve the

security of the product they make and maintain. The result can be reduced systemic

risk for U.S. networks.

The success of the program is vitally dependent upon the awareness of the individuals

and businesses that take advantage of it. Consumer education enables stakeholders 

to make informed decisions about product selection and helps to differentiate 

trustworthy products in the marketplace. Of course, industry participants recognize

that they have a role to play in educating the public. Manufacturers will likely include

information about the Mark with products; retailers will likely train sales associates to

help customers.

But a public service advertising campaign is required as well. This PSA campaign must

be broad and effective enough to create high Mark recognition among the U.S. 

population. Such results are beyond the reach of manufacturers and retailers. The U.S. 

government must take a leading role.

A multi-year campaign and funding on par with that of Energy Star is required. For

this, Congress must step in to ensure adequate and continuing funding for a 

consumer education campaign.

Enabling Recommendation ER3.1.6: The government should establish 

appropriate U.S. representation regarding international harmonization of 

IoT cybersecurity programs and requirements as such programs are 

established for domestic market sectors. 

Supported by Finding x.x

The U.S. Department of State must prioritize supporting the Mark program owner, 

NIST and stakeholders in the relevant private sector for each of the various U.S. 

cybersecurity trust certification programs, in conjunction with relevant agencies, to 

engage allies and partners toward harmonizing standards and pursuing mutual 

recognition of the U.S. Cyber Trust Mark and similar labeling efforts. 
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In Consumer IoT, the FCC’s U.S. Cyber Trust Mark is the subject of a joint agreement 

between the U.S. and the EU. In October 2023, the two governments released a Joint 

Statement covering many areas of agreement. For consumer cyber protection, the 

Statement says,

“[We] commit to work together on achieving mutual recognition for our 

government-backed cybersecurity labeling programs and regulations for 

Internet-of-things devices aiming at a Joint CyberSafe Products Action Plan.”[ref. 

https://www.whitehouse.gov/briefing-room/statements-releases/2023/10/20/u-seu-summit-joint-statement/ @ 28] 

Subsequently, the Biden Administration announced a roadmap to that end 

[https://broadbandbreakfast.com/2024/01/ces-2024-biden-administrationannounces-deal-with-eu-on-cyber-trust-mark/].It is expected that the consumeroriented U.S. Cyber Trust Mark at the FCC is the first of multiple sector-specific IoT 

cybersecurity programs. Other examples may be smart energy or industrial IoT. 

Harmonization of U.S. programs with those of other nations is key to global relevance 

and success. 

Going forward, NIST, as the central agency of IoT cybersecurity expertise, should be 

part of such harmonization discussions. As program ownership is determined, as is 

the case of FCC with the U.S. Cyber Trust Mark, that program owner should also be 

deeply involved in harmonization discussions. State, with international relationship 

responsibility, can assist in convening or coordinating.

Enabling Recommendation ER3.1.7: The government should recognize and 

promote existing standards, and conformity assessment schemes that 

facilitate cybersecurity in industrial IoT applications.

Supported by Finding x.x

The U.S. Cyber Trust Mark program is specific to consumer IoT. Cybersecurity postures

vary depending on the type of product produced and its intended market audience 

and use, thereby complicating the creation of a comprehensive or one-size-fits-all

solution in relaying the security level of a product. The industrial IoT sector primarily

utilizes operational technology (“OT”) systems and products. OT is comprised of

hardware and software that detects or causes a physical change through the direct

monitoring and/or control of industrial equipment. OT devices are those that are not

broadly defined as ‘consumer’ due to their usage in commercial operations and are

not available or readily available for sale to the public.
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There exist numerous standards and conformity assessment schemes related to

industrial OT systems and smart manufacturing, such as the IEC 62443 series of

standards and conformity assessment programs. The IEC 62443 program is mature,

well-respected, and already has multiple certifying programs such as ISASecure.org.

The UL 2900 series of standards is another suitable program. These standards and 

certification programs provide a systematic, practical, and holistic approach to

addressing cybersecurity.

Implementation Considerations:

• These existing standards and conformity assessment schemes can 

demonstrate cybersecurity compliance by a number of methods based on a 

risk assessment. They can include a manufacturer self-attestation that the

product or device complies to a certain cybersecurity standard, documentation

that the product or device uses a Secure Development Life Cycle that places

security front and center during the product development, or third-party 

testing compliance via a Nationally Recognized Testing Laboratory.

• NCCoE or similar public-private agency groups should be considered for

programs to highlight usage of selected standards.

• International harmonization and alignment should be pursued to the greatest

extent possible

Data Privacy Regulation

Key Recommendation KR3.2: Congress should pass comprehensive federal 

privacy legislation. 

Supported by Finding x.x

To address the growing complexities and uncertainties surrounding data privacy in

the United States, a key recommendation has been proposed to the U.S. government:

the support of a comprehensive Federal Data Privacy Regulation. This initiative seeks

to support the establishment of uniform standards for data privacy across the nation,

aiming to harmonize the existing patchwork of State privacy regulations. The primary

motivation behind this recommendation is to reduce the complexity and legal

uncertainty currently faced by businesses, which often have to navigate a labyrinth of

varied State laws regarding data collection, storage, use, and sharing.

To effectively implement this regulation, several challenges need to be considered. 

These include addressing four key aspects of data privacy - collection, storage, use,

and sharing - and carefully considering the costs associated with implementing and 

enforcing the new regulation. Additionally, there needs to be a well-thought-out
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transition period and set compliance deadlines for businesses presently operating

under various State laws. 

However, implementing a comprehensive Federal Data Privacy Regulation is not

without challenges. The U.S. government is likely to face legislative gridlock and 

potential opposition from various interest groups. Managing preemption and the

private right of action will be crucial, along with the need for inter-agency cooperation.

Several agencies could be pivotal in championing this recommendation, including

the Federal Trade Commission (FTC), the Department of Commerce, and the House

Committee on Energy and Commerce.

Enabling Recommendation ER3.2.1: Congress should include IoT in 

proposed comprehensive privacy legislation.

Supported by Finding x.x

To enhance privacy standards and foster innovation in the rapidly evolving realm of 

the Internet of Things (IoT), the U.S. government should include IoT considerations, 

including IoT data retention and transparency, in any future proposed Federal privacy 

regulations. Adding specific provisions regarding IoT Data Retention and 

Transparency. It aims to establish clear guidelines for manufacturers on the duration 

of data retention for business, government, and consumer data. This move is intended 

to align with existing or future Federal privacy legislation by integrating IoT-specific 

language related to data retention.

This recommendation ensures that IoT device manufacturers adhere to a consistent 

set of privacy standards and yet benefit from a resolution of current uncertainties in 

the domestic marketplace. This consistency is pivotal in enhancing the trust and 

protection of data across business, government, and consumer sectors. Moreover, the 

recommendation aims to stimulate innovation by providing IoT businesses with clear 

guidelines and expectations, fostering a competitive and growth-oriented 

environment.

Data and Privacy Policy

Key Recommendation KR3.3: The White House and Congress should 

facilitate/support the development of a Data and Privacy Policy 

Framework. 

Supported by Finding x.x
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The White House and Congress should facilitate/support the development of a Data 

and Privacy Policy Framework that clearly considers the different aspects of privacy 

and confidentiality including transparency and control over data collection and usage 

for individuals, and data confidentiality for organizations.

The resulting framework would consider the different aspects of privacy and 

confidentiality including transparency and control over data collection and usage for 

individuals, and data confidentiality for organizations. data (i.e., machine versus 

personal) and how they should or shouldn’t be utilized in smart transportation 

technologies.

The justification for this recommendation stems from the need for a consistent and 

unified approach to data, privacy, and security within the IoT sector. This move will 

reduce confusion and fragmentation for businesses, government entities, and 

consumers. Acknowledging the advancements in privacy legislation by several U.S. 

States, this framework also seeks to encourage innovation by providing clear 

guidelines and expectations for IoT device manufacturers, thus fostering a 

competitive and growth-oriented environment.

However, implementing such a framework comes with its considerations and 

challenges. The U.S. government is advised to draw lessons from existing privacy 

regulations to create an effective and efficient framework. This framework must 

remain adaptable and scalable to keep pace with the rapidly evolving nature of IoT 

technology and the data privacy landscape.

One of the key challenges in implementing this framework is balancing the 

protection of data privacy for businesses, government, and consumers while 

simultaneously fostering innovation in the IoT sector. Additionally, the government 

needs to provide adequate resources, guidance, and support to businesses to adopt 

and implement this framework. Regular review and framework updates are essential 

to ensure its relevance and effectiveness in addressing emerging data privacy 

challenges and technological advancements.

Congress is identified as a possible participating body that could assist or champion 

this recommendation. For successful implementation, the U.S. Federal government 

should consider working closely with States that have already embraced privacy 

frameworks or are advancing regulations. This collaboration is vital for regulatory 

alignment. The government is also encouraged to utilize strategies from the National 

Cybersecurity Strategy Implementation Plan of July 2013, particularly initiatives 

focused on cyber regulatory harmonization and increasing agency use of frameworks 

and international standards for regulatory alignment.
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For example, data generated from a connected vehicle and its corresponding 

roadside infrastructure can be utilized to transmit basic safety information to the 

vehicle's driver such as entering a school or work zone. Emergency Vehicles and 

corresponding roadside infrastructure can generate data to preempt traffic signals so 

the vehicles can get to their destination sooner.

While the vast amount of data that would be provided will significantly improve safety 

and convenience, the criticality and sensitivity of such data require adequate 

protection that can be specified through this new framework.

Implementation considerations: In conjunction with supporting a National Privacy 

Framework, the federal government should consider setting high-level policy 

guidelines for data ownership, retention and usage that include specific guidance for 

data that has personal information. These guidelines should leverage existing 

legislative or regulatory language and provide incentives for state and local 

jurisdictions to adopt them. The creation of a model and guidelines for data 

ownership, retention and usage would provide states and local jurisdictions the ability 

to develop criteria for how long data should be retained, how personal information 

should be stripped from any such data, and how to effectively utilize that data in their 

operations.

As the framework is implemented broadly, constituents could share lessons learned 

from pilot projects and successful case studies, further supporting training and 

education on proper data retention and usage procedures.

Enabling Recommendation ER3.3.1: The government should promote 

"Privacy by Design" in IoT device development, deployment, and 

implementation. 

Supported by Finding x.x

In the realm of IoT (Internet of Things), the U.S. government is recommended to adopt 

and promote the "Privacy by Design" (PbD) approach in the development, 

deployment, and implementation of IoT devices. This recommendation is in line with 

the U.S. National Strategy to Advance Privacy-Preserving Data Sharing and Analytics 

(PPDSA) as of March 2023 and the National Cybersecurity Strategy Implementation 

Plan of July 2013. The latter particularly emphasizes scaling public-private 

partnerships to develop and adopt technologies that are secure by design and default.

The rationale behind this recommendation is multifaceted. Firstly, it aims to minimize 

data privacy risks and the ensuing legal complications, thereby aligning IoT privacy 

practices with international data protection standards. Additionally, the approach 
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serves to educate both businesses and consumers about privacy in IoT, providing 

incentives to companies that comply with PbD guidelines.

Implementing this recommendation, however, comes with its own set of challenges. 

These include the difficulty in monitoring a diverse and constantly evolving range of 

IoT applications and potential resistance from the private sector, which might 

perceive PbD implementation as risky or costly. Another significant challenge is 

developing universally accepted privacy standards for IoT. 

For the successful execution of this recommendation, the involvement of key U.S. 

government agencies is essential. The Office of Science and Technology Policy (OSTP), 

the National Institute of Standards and Technology (NIST), and the Federal Trade 

Commission (FTC) are identified as critical players in championing this 

recommendation.

To effectively implement PbD in IoT, the U.S. government needs to consider several 

factors. These include the development of clear PbD guidelines and the provision of 

incentives to companies that comply. It's also important to ensure the adaptability of 

these principles across various IoT devices and to align them with international privacy 

standards. Support for small and medium enterprises (SMEs) in adhering to these 

principles is crucial, as is the regular evaluation and refinement of guidelines and 

incentives. It should be noted that cybersecurity technology supports privacy policy, 

in the “confidentiality” element of the cybersecurity CIA trilogy (confidentiality, 

integrity and availability). Therefore, the government should also continue to leverage

the National Cybersecurity Strategy Implementation Plan to drive the development 

of secure-by-design technology through public-private partnerships.

Enabling Recommendation ER3.3.2: The government should establish clear 

policies for third-party data sharing and IoT device data use

Supported by Finding x.x

In response to IoT devices' growing interconnectivity and data-sharing capabilities, 

which pose significant privacy risks, the U.S. government is recommended to establish 

clear policies for third-party data sharing and IoT device data use. This 

recommendation includes outlining IoT manufacturers' and service providers' 

responsibilities and obligations when dealing with third-party entities, emphasizing 

the importance of user consent and secure data practices. 

The rationale for this recommendation stems from the need to safeguard consumers’' 

personal data and ensure transparency in how this data is shared and used. By 

establishing clear policies, the government can foster trust among users and 
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encourage wider adoption of IoT technologies. These policies are expected to 

communicate third-party data sharing and usage in privacy policies and be supported 

by public awareness campaigns to educate users about their data rights. 

The U.S. government should consider working with industry leaders to establish data 

use guidelines, leveraging the National Cybersecurity Strategy Implementation Plans 

from July 2013. These include Initiative Number 1.1.1, focusing on cyber regulatory 

harmonization, and Initiative Number 1.1.3, which aims to increase agency use of 

frameworks and international standards for regulatory alignment.

Agencies within the U.S. government, including the National Institute of Standards 

and Technology (NIST), the Federal Trade Commission (FTC), the Department of 

Energy (DOE), the United States Department of Agriculture (USDA), and the Office of 

the National Cyber Director (ONCD), are identified as key players who could assist or 

champion the recommendation, contributing to the establishment of a more secure 

and transparent IoT ecosystem.

Enabling Recommendation ER3.3.3: The government should encourage the 

use of plain language in IoT privacy policies.

Supported by Finding x.x

In IoT and privacy, a crucial recommendation for the U.S. government is adopting 

plain language in privacy policies. This recommendation, stemming from the Internet 

of Things (IoT) Cybersecurity Improvement Act of 2020, focuses on integrating plain 

language into privacy policies. The goal is to simplify privacy policies, notices, and data 

use policies, making them more accessible and understandable to users. This initiative 

aligns with the "Plain Writing Act of 2010" (Public Law 111-274), which the government 

can use to model this recommendation on organizations providing IoT technology to 

the government.

The justification for this recommendation lies in its potential to improve user 

understanding of data privacy policies, thereby leading to more informed decisions 

regarding IoT device usage. Additionally, it aims to enhance public trust in IoT devices 

and related technologies, and simplified policies could result in increased compliance 

and fewer legal disputes.

Implementing this recommendation requires the U.S. government to develop 

guidelines and best practices for organizations on simplifying privacy policies. It 

involves establishing criteria for evaluating the readability of these policies and 

coordinating with various stakeholders, including the private sector, business, 

government, and consumer data advocacy groups, to ensure widespread adoption. 
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For effective implementation, the U.S. Federal government should consider creating 

contractual requirements for IoT providers to implement simplified privacy policies in 

government procurement. This can be achieved by utilizing the National 

Cybersecurity Strategy Implementation Plan of July 2013, particularly Initiative 

Number 3.2.1, related to the IoT Cybersecurity Improvement Act of 2020, and Initiative 

Number 1.1.1, focused on cyber regulatory harmonization. The Plain Writing Act of 2010 

is also a foundation for this recommendation.

Privacy Protections and Transparency for IoT

Enabling Recommendation ER3.3.4: The government should develop and 

implement privacy transparency mechanisms. 

Supported by Finding x.x

In the evolving landscape of IoT and privacy, the U.S. government is poised to take a 

significant step forward with the recommendation of establishing a comprehensive 

privacy transparency system for IoT devices. This initiative, drawing inspiration from 

other transparency frameworks, is designed to significantly empower various 

stakeholders – businesses, governments, and consumers – by providing them with 

detailed insights into the privacy features and practices of IoT devices. This move is 

anticipated to enhance general awareness and stimulate IoT manufacturers to 

prioritize privacy, thereby fostering innovation and competition in the development 

of privacy-enhancing technologies.

For the successful deployment of this system, the government needs to consider the 

perspectives of privacy experts, industry stakeholders, and advocacy groups. It is 

essential to develop clear guidelines and standards for privacy transparency, including 

what information should be included, its format, and how it should be presented. It is 

also crucial to motivate IoT device manufacturers to adopt this system, supporting 

them in aligning with these new recommendations.

However, challenges such as ensuring widespread adoption and compliance across 

different industries, motivating manufacturers, and balancing comprehensive 

information with simplicity and understandability need to be addressed. Key agencies 

like the Department of Commerce, the National Institute of Standards and 

Technology, and the Federal Trade Commission could play instrumental roles in 

driving this initiative forward.

Additionally, the government's strategy should promote the benefits of IoT privacy 

transparency, forging partnerships with industry leaders to develop this system and 

leveraging existing initiatives under the National Cybersecurity Strategy 
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Implementation Plan. These steps would establish a robust framework for IoT privacy 

and significantly contribute to enhancing cybersecurity and data protection in the 

digital era.

Enabling Recommendation ER3.3.5: The government should endorse 

universal opt-out signals for IoT devices and companion apps.

Supported by Finding x.x

In an initiative to bolster privacy and data protection in the Internet of Things (IoT) 

realm, the U.S. government is recommended to endorse Universal Opt-Out Signals for 

IoT devices and their companion apps. This proposal is driven by the growing need to 

safeguard user privacy in an increasingly interconnected digital world. Adopting 

Universal Opt-Out Signals would simplify the process for consumers, enabling them 

to easily manage their privacy settings across various IoT devices and applications. 

However, implementing this recommendation is not without its challenges. The 

government must consider the technical feasibility of applying these universal optout signals across various devices and apps and the associated costs of establishing 

and enforcing such a system. Standardized guidelines or legislation may be necessary 

to ensure uniform adoption of the Universal Opt-Out Signals.

Resistance from IoT manufacturers and app developers is anticipated, primarily due 

to the potential costs and complexities of implementing these signals. Additionally, 

the technological constraints of harmonizing these signals across different platforms 

and devices pose a significant challenge. Another crucial aspect is effectively 

communicating to consumers how Universal Opt-Out Signals can facilitate easier 

management of their privacy rights. 

Several agencies within the U.S. government could play pivotal roles in championing 

this initiative, including the Federal Trade Commission (FTC), the National Institute of 

Standards and Technology (NIST), the Federal Communications Commission (FCC), 

and the Department of Commerce. 

In formulating the implementation strategy, the government should consider 

leveraging existing frameworks and regulations. This includes the National 

Cybersecurity Strategy Implementation Plan of July 2013, which suggests initiating a 

U.S. Government IoT security labeling program. Furthermore, existing privacy laws like 

the California Consumer Privacy Act (CCPA) and its amendment, the California Privacy 

Rights Act (CPRA), along with the Colorado Privacy Act (CPA) and the Connecticut 

Data Privacy Act (CTDPA), provide valuable precedents for enforcing privacy 

provisions starting from 2024. These laws and initiatives could serve as models for 
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developing a comprehensive and effective system of Universal Opt-Out Signals in the 

IoT space. 

Enabling Recommendation ER3.3.6: The government should require IoT 

Privacy information on new car automobile “Monroney Stickers”. 

Supported by Finding x.x

In the landscape of connected automobiles, where privacy concerns are mounting, a 

crucial recommendation has been presented to the U.S. government: including IoT 

Privacy Information on "Monroney Stickers" for new and used cars. This 

recommendation aims to leverage the traditional role of Monroney Stickers – known 

for detailing fuel efficiency and safety ratings – to now also disclose vital information 

about IoT privacy. This encompasses data collection, retention, sale, and the 

availability of a universal opt-out feature.

This initiative is primarily driven by the need to enhance consumer protection and 

address growing concerns over personal data use and sharing by IoT devices in 

automobiles. The urgency of this issue is highlighted by findings from the Mozilla 

Foundation's Automobile Privacy Report in 2023, which reveals that all 25 car brands 

reviewed in this report collect personal data, with most sharing or selling this 

information. The report further indicates that most brands offer limited control over 

drivers' data, and many have concerning records regarding privacy breaches. Notably, 

the report notes that none of the car brands reviewed that participate under the 

Alliance for Automotive Innovation adhere to voluntary consumer protection 

principles focusing on data privacy.

However, the path to implementing this recommendation involves overcoming 

several hurdles. It requires a standardized, straightforward, and concise method to 

present IoT privacy information, ensuring compliance with existing privacy laws and 

adaptability to future technological developments. The U.S. government must also 

prepare for possible resistance from automakers concerned about cost implications, 

the task of educating consumers about the importance of this information, and the 

complexity of the regulatory landscape governing IoT and privacy. 

A united effort from various U.S. government agencies is imperative to successfully 

implement this recommendation. Agencies such as the Federal Trade Commission 

(FTC), National Highway Traffic Safety Administration (NHTSA), Federal 

Communications Commission (FCC), Department of Transportation (DOT), and the 

Cybersecurity and Infrastructure Security Agency (CISA) could play critical roles. Their 

involvement would uphold the principles of the Automobile Information Disclosure 
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Act of 1958 and significantly bolster consumer rights in an era increasingly defined by 

connected technology.

Enabling Recommendation ER3.3.7: The government should add "Location 

Tracking Enabled" notice to U.S. E-labeled IoT devices.

Supported by Finding x.x

In a move to enhance consumer awareness and data privacy in the IoT sphere, a 

pivotal recommendation has been proposed to the U.S. government. It focuses on 

incorporating a clear and upfront notification within the U.S. e-labeling program for 

IoT devices, specifically stating, "Notice: Precise location tracking is enabled by default 

on this device." This recommendation emerged from a deep-seated belief in 

transparency and informed consent. Consumers, often unknowingly, have their 

location data collected and shared by various IoT devices. This straightforward 

Statement aims to inform consumers about this data collection practice immediately.

The justification for this recommendation is threefold. Firstly, it upholds the 

consumer's right to know if and how their location data is tracked. Secondly, it 

emphasizes the ethical imperative of informed consent in data collection, ensuring 

that consumers know these practices without navigating complex privacy policies. 

Lastly, this recommendation aligns with various data protection regulations 

advocating transparency and informed consent. 

However, implementing this recommendation poses several challenges and 

considerations. The U.S. government needs to standardize the Statement's wording 

and visibility to consumers as part of the U.S. e-labeling program. It is crucial to assess 

the technical feasibility of how and where this notice will be displayed—be it on the 

physical device, a website, or an associated app—for effective consumer awareness. 

Moreover, robust systems for audits and compliance must be established to ensure 

adherence to this notification requirement.

Enabling Recommendation ER3.3.8: The government should promote the 

use, development, and implementation of Privacy-Enhancing 

Technologies (PETs) in IoT systems.

Supported by Finding x.x

In the realm of IoT, the U.S. government is recommended to champion the 

implementation of Privacy-Enhancing Technologies (PETs). These technologies are 

vital in safeguarding privacy while still harnessing valuable insights from the 

expansive IoT data. PETs align with responsible data use principles and bolster trust 
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and acceptance of IoT solutions across society. Their adoption is crucial for preventing 

data breaches and the ensuing legal complications. 

However, the path to implementing PETs is not without challenges. The government 

needs to ensure robust security measures are in place to avert unauthorized data 

access and conduct thorough technical and ethical evaluations before adopting these 

technologies. It's also essential to enhance public understanding and trust in PETs 

and encourage interoperability among different PET systems is also essential. 

Developing a framework to monitor PETs' effectiveness and impacts in the IoT 

environment.

One of the primary hurdles in this endeavor is the resistance from the private sector, 

often stemming from perceived risks or costs associated with PET integration. A U.S. 

government initiative that not only promotes PETs but also offers guidelines and 

support could be instrumental in helping manufacturers. Such an initiative would 

facilitate the production of more privacy-conscious IoT devices, thereby reinforcing 

the security and trustworthiness of IoT systems in the eyes of users and manufacturers 

alike.

Enabling Recommendation ER3.3.9: The government should follow NIST 

sanitization standards for government automobiles before resale, and 

should encourage NIST sanitization standards for automobiles before 

resale.

Supported by Finding x.x

Follow NIST sanitization standards for government automobiles before resale: 

In enhancing privacy and security in the used automobile sector, the U.S. government 

faces a crucial recommendation: to mandate that car seller organizations adhere to 

the National Institute of Standards and Technology's (NIST) media sanitization 

guidelines before reselling vehicles. This recommendation aligns with the e-Stewards 

Standard, supported by the Environmental Protection Agency (EPA) Recycling 

Program. The core objective is to protect consumer privacy and prevent unauthorized 

access to sensitive data that modern vehicle systems often store.

The implementation of this recommendation, however, is not without its challenges 

and considerations. The U.S. government must account for the financial implications 

for car sellers, who would bear the cost of implementing these sanitization standards. 

Additionally, there's a need for comprehensive training and awareness programs to 

familiarize car sellers with the NIST guidelines. The technological infrastructure to 
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support these sanitization processes is another vital consideration, along with robust 

mechanisms for monitoring and ensuring compliance.

For the successful execution of this recommendation leverage existing frameworks 

and standards for a successful implementation. This includes utilizing the National 

Cybersecurity Strategy Implementation Plan, specifically Initiative Number: 1.1.3, 

which focuses on increasing agency use of frameworks and international standards 

for regulatory alignment. NIST Special Publication 800-88 provides a foundation that 

can be further expanded. Additionally, aligning with the EPA’s implementation of 

Electronics Recycling Standards, particularly R2, and e-Stewards, will ensure a 

comprehensive approach to sanitizing and reselling used automobiles.

Encourage NIST sanitization standards for automobiles before resale:

In response to the emerging privacy and security challenges associated with the 

resale of government automobiles equipped with IoT technologies, a significant 

recommendation has been proposed: Mandating NIST Sanitization Standards for 

Government Automobiles Before Resell. This narrative encapsulates the key aspects 

of this recommendation.

The U.S. government is advised to ensure that before reselling, all agencies adhere 

strictly to the media sanitization guidelines set forth by the National Institute of 

Standards and Technology (NIST) before reselling. This requirement is not just a 

procedural formality but a critical step to safeguard consumer privacy and prevent 

unauthorized access to sensitive information that might be stored in modern vehicle 

systems. Such an approach aligns with the e-Stewards Standard, supported by the 

Environmental Protection Agency (EPA) as part of its Recycling Program.

The proposal to require sanitization for resale of government automobiles represents 

a comprehensive approach that combines regulatory alignment, technological 

solutions, and human resource training. It is a concerted effort to enhance data 

security, align with environmental standards, and ultimately protect consumer 

privacy in the age of IoT.

.
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ey ecommendation .: he government should support trusted architectures and conduct a limited pilot to assess the value of trusted digital threads for provenance and traceability across the supply chain.

Supported by Finding x.x

The government should support creation of cryptographically strong architectures 

and infrastructure that enable supply chain provenance, traceability, and lifecycle 

management by linking hardware and software bill of materials to the design and 

manufacturing processes delivering trusted assets and data.

This should incentivize suppliers to develop trusted architectures for supply chain 

provenance, traceability, assurance of supply and IoT product lifecycle management. 

By cryptographically linking trusted SBOM141 to trusted HBOM142 in any IoT device or 

system, industries can help mitigate the risks associated with supply chain security, 

compromised components, and ensure the security and reliability of critical systems. 

This will strengthen national security, public safety, and economic stability, making it 

a valuable investment for the government and society such that: 

• The use of trusted architectures for supply chain provenance and traceability 

can help mitigate the risks associated with vulnerabilities or compromised 

components.

• Trusted architectures for supply chain provenance and traceability can increase 

the trustworthiness of critical IoT systems, which is key for national security, 

public safety, and economic stability. 

• Trusted architectures linked to Cyber Trust Mark143 can increase consumer 

confidence in the products they purchase and prevent supply chain attacks 

and data breaches leading to greater economic benefits for businesses.

• Cryptographic linking of SBOM to trusted HBOM enhances supply chain 

security, visibility, chain of custody and product lifecycle management. (and 

overall user confidence).

• Trusted HBOM and SBOM assets and related data can form the basis of trusted 

digital threads which also enable trusted IoT applications and data for AI based 

digital twins.

Implementation Considerations

• Educate stakeholders in the supply chain on the benefits of using trusted 

architectures for supply chain provenance and traceability. 

141 Software Bill of Materials for Electronic parts and Software modules used in the assembly of a device or complex 

system. 

142 Hardware Bill of Materials must include a Root of Trust with a source of Entropy such for security and unique ID 

(fingerprint). 

143 The US Cyber Trust Mark all you need to know https://www.iotforall.com/u-s-cyber-trust-mark-all-you-need-toknow 
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• Promote industry adoption of trusted architectures through education and 

outreach. Incentivize hardware suppliers to develop trusted architectures that 

enable supply chain provenance and traceability and promote them with the 

Cyber Trust Mark. 

• Develop guidelines for how the trusted architectures should be implemented 

by linking HBOM and SBOM with DBOM144 to facilitate provenance and 

traceability and encourage the adoption of standards and best practices. 

• Foster collaboration between government agencies and industry stakeholders 

(Private-Public Partnerships) to develop and promote trusted architectures 

that support secure protocols for provisioning and market access. 

Enabling Recommendation ER3.4.1: The government should incentivize 

multi-stakeholder alliances and collaboration for trusted end-to-end 

solutions across supply chains. 

Supported by Finding x.x

The federal government should implement incentives to promote collaboration for 

trusted end to end solutions, including enterprise business processes and workflows 

cryptographically linking tasks, personas, and handoffs of acids and data and we're 

participating stakeholders. Incentivizing IoT supply chains to adopt trusted 

digitalization solutions with cryptographic tracing capabilities is strategic to 

enhancing national security, stimulating economic growth, and positioning the US as 

a global leader in IoT technology. The term “trusted” indicates that IoT parts, systems, 

applications, and supply chains operate as intended and produce data that is not 

tampered or compromised. 

This will allow industries to adopt additional capabilities for tracing design, 

manufacturing, and enterprise workflows that cryptographically link parts, personas, 

and data to deliver traceable products and IoT systems that function and perform as 

originally intended. The federal government’s active role in promoting these 

capabilities can contribute to more resilient supply chains and valuable end-to-end 

solutions, that benefit societies and industry ecosystems. By encouraging industries 

to pursue trusted digitalization solutions, the government can strengthen national 

security and accelerate adoption and growth to: 

• Ensure the confidentiality and integrity of IoT electronics supply chains to 

prevent cyber-attacks in critical infrastructure and protect against human and 

economic losses.

144 Digital Bill of Materials consisting of HBOM, SBOM plus info on quality, reliability, and workflow process.
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• Accelerate IT/OT convergence with adoption of trusted traceability methods for 

the electronics value chain that enhance the effectiveness of critical 

infrastructure services.

• Enable companies and businesses to foster innovation, create a competitive 

advantage with smart-connected IoT Systems to become smart-connectedsecure suppliers.

• Enable the creation of trusted ecosystems that accelerate end-to-end 

innovation, monetization, and growth of IoT-enabled digital economies. 

Implementation Considerations

• Offer tax credits, grants, or other financial incentives to companies that market 

electronics products with traceable parts Country of Diffusion and Country of 

Origin145, provenance, and journey in the supply chain.

• Require contractors and suppliers to adhere to specific security and traceability 

standards when bidding on government contracts, particularly for critical 

infrastructure.

• Establish a certification process for electronics and IoT products that meet 

security and traceability standards to improve trust in value chains, linked to 

cybersecurity labels. 

• Engage industry associations and other stakeholders to develop best practices 

and guidelines for trusted electronics and IoT systems development and supply 

chain. 

Enabling Recommendation ER3.4.2: Support collaborative IoT platforms 

that align stakeholder business incentives.

Supported by Finding x.x

The government should support collaborative IoT platforms that align the business 

incentives of stakeholders to foster innovation, enable orchestration and while 

harnessing the power of network effects to enhance security, user experience and 

drive economic growth.Collaborative IoT platforms encourage industry-wide 

innovation, leading to the development of cutting-edge technologies and solutions. 

These platforms streamline device management, data exchange, and interoperability, 

reducing operational complexities. By aligning business incentives, stakeholders are 

motivated to prioritize cybersecurity resulting in safer IoT environments. IoT-driven 

industries will experience substantial growth, creating jobs, and contributing to 

145 Country of Diffusion where a part is fabricated and Country of Origin where the product made of parts is assembled.
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economic prosperity. This approach will significantly benefit the nation by enhancing 

security, improving the user experience, and driving economic growth. 

Implementation Considerations:

• Standardization: Define industry standards to ensure compatibility and 

interoperability across IoT platforms.

• Public-Private Partnerships: Foster collaboration between government 

agencies, businesses, and academia to drive innovation.

• Data Privacy and Confidentiality: Establish robust data protection regulations 

to build trust and protect user data. 

• Incentive Mechanisms: Create incentives like tax benefits and grants to 

motivate businesses to align their incentives with IoT platform goals.

• Monitoring and Evaluation: Implement a monitoring system to track progress, 

security, and the impact on economic growth.

Enabling Recommendation ER3.4.3: The government should encourage 

the use of digital threads for connected supply chains. 

Supported by Finding x.x

Promote the use of digital threads146 among enterprises in disaggregated supply 

chains, to enable the creation of connected IoT supply chains. Leverage digital threads 

of data across value chains to enable marketplaces of trusted data producers and data 

consumers.

The government should support the development of digital threads across supply 

chains by incentivizing companies to digitalize their workflows, link their internal data 

IDs and Bills of Materials to identifiers and data to create trusted (certified) digital 

threads that can enable trusted digital marketplaces of producers, consumers, and 

platform-based business ecosystems. Business platforms for data exchange can have 

a significant impact on improving supply chain visibility, efficiency, security, and 

growth. Digital threads may extend from supply chains to the field use of IoT devices 

and connected ecosystems of data marketplaces. 

Linking digital threads for HBOM, SBOM, DBOM across supply chains can accelerate 

adoption in ways that protect proprietary IP while enabling new digital marketplaces. Digital 

threads enable marketplaces of data producers and data consumers, creating new business 

opportunities for revenue streams that will fuel the digital economies. This increased end-to146 Digital flow of data connecting business processes products assets and bill of materials in a value chain. For the 

electronics value chain the digital threat includesof HBOM, SBOM and other Digital Bill of Materials (DBOM)
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end visibility of a product's lifecycle and supply chain transparency can help reduce risk of 

cyberattacks, counterfeiting, and product recalls. Companies that adopt a digital thread can 

improve supply chain efficiency, reduce costs, manage vulnerabilities, increase 

differentiation, and promote innovation.

Implementation Considerations

• Develop educational and training programs to help businesses implement 

digital threads. Establish guidelines for creating a digital thread, including 

standards. 

• Incentivize companies to digitalize their workflows through tax credits, grants, 

or subsidies for investing in digital technologies. Encourage PPP collaboration. 

• Leverage the Cybersecurity labeling program to create a digital trail for BOM 

(DBOM, HBOM, SBOM, Security keys, certificates etc.) for IoT systems by vertical 

market.

• Provide funding for research and development of methods and standards to 

facilitate development of best practices and guidelines for implementing 

digital threads.

Enabling Recommendation ER3.4.4: The government should facilitate the 

creation of business ecosystems that enable new business models and 

revenue streams

Supported by Finding x.x

As data produced in connected supply chains and during field or IoT devices and 

becomes the “new gold”, the government should raise awareness about the value of 

digital or data business ecosystems and trusted data-driven digital threads that will 

enable new business models. 

Digital networks of interconnected businesses, technologies, and platforms can 

leverage synergies to enhance existing products, enable digital twins and drive 

growth through XaaS49 business models. 

The federal government should raise awareness about the New Gold, Data 

Monetization Strategies, Data Analytics for Insights, Trusted Data Marketplaces, 

Platform-based Business Ecosystems, Network effects, Digital Thread of Data in 

connected supply chains, Data Regulations, and tools for Monitoring and Managing 

Data Marketplaces. 

This includes:
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• Data-driven ecosystems that can create new revenue streams and enhance 

existing products and services among Interconnected businesses, 

technologies, and platforms that can leverage synergies in the value chain. 

• Data analytics that can provide insights that drive innovation, improve 

decision-making, and enable data monetization strategies. This can lead to 

significant benefits across value chains and drive economic growth. 

• Trusted digital marketplaces that can promote data sharing and collaboration 

and business ecosystems can lead to new revenue streams and enhanced 

products and services. 

• Platform-based ecosystems made of connected businesses that can 

collaborate and innovate more effectively. They can also scale rapidly through 

network effects and can drive sustainable growth for businesses and value 

chains. 

• Data regulations that can provide a framework for businesses to manage and 

use data responsibly and using tools for monitoring and managing trusted 

digital marketplaces that ensure transparency and accountability. 

Implementation Considerations

• Develop educational programs for businesses and individuals. Raise awareness 

about business ecosystems through public campaigns, conferences, and 

workshops.

• Provide funding and incentives for data-driven ecosystem and solutions PPPs 

with industry leaders, innovative startups, and academic institutions.

• Foster the development of orchestrated platform-based business ecosystems 

supporting networks effects by providing incentives and resources to 

businesses.

• Encourage collaboration and innovation by promoting the value network 

effects. Provide tools and resources for monitoring and managing data 

marketplaces. 

Enabling Recommendation ER3.4.5: The government should promote 

consistent levels of IoT device hardware and software identity 

documentation information included in trusted digital threads for 

Software IoT supply chains.

Supported by Finding x.x

Establish a centralized IoT Device Registry to standardize due diligence, enhancing 

IoT device validation, security, and maintenance. This promotes transparency, 
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sustainability, and economic growth by fostering accountability, efficient IoT 

management and new business models. 

The Federal government should initiate the development of a centralized IoT Device 

Registry to standardize due diligence processes for IoT devices, capturing vital data 

points necessary for their validation, security, and maintenance. This comprehensive 

approach aims to enhance transparency, sustainability, and economic growth by 

fostering innovation, accountability, and efficient management within the IoT 

ecosystem. The proposed registry would facilitate collaboration, risk mitigation, and 

timely vulnerability notifications, benefitting businesses, the environment, and the 

broader digital economy.

Implementation Considerations:

• Regulatory Framework: Develop regulations to mandate IoT device 

manufacturers to provide comprehensive Software Bills of Materials (SBOMs) 

during firmware and OS updates.

• Centralized Database: Create a centralized database to correlate vulnerable 

software and hardware components with IoT modules and devices, updated 

regularly.

• Device Management Systems: Implement reporting mechanisms for device 

management systems, over-the-air updates, and remote monitoring services.

• Subscription Model: Enterprises would pay a subscription fee to register their 

devices, ensuring continued access to registry information.

Key Recommendation - AI
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Fostering an IoT-Ready Workforce

Objective 4: The U.S. should invest in and promote initiatives that will improve the 

knowledge, skills, and abilities of those who develop, implement, and operate IoT 

devices, applications and systems.

Key Recommendation KR4.1: The government should invest in and 

promote IoT-related aspects of education and workforce. 

Supported by Finding x.x

Workforce and education are broad topics. Specialized training programs could start 

as early as high school and include cybersecurity topics. Inclusion of yearly 

certifications is encouraged. 

Benson note: When we talk about IoT workforce development, we need to think more 

broadly - we need to think about and discuss it this way. The IoT workforce 

development approach should consider and include: 

1. Sourcing and recruitment of workers: creating initiatives to bring more people 

in the workforce. This could be new workers (out of high school, out of college, 

immigration, and people who have left the workforce - the unemployed, 

retired, women who left to raise kids and now coming back, etc.), as well as 

people who have traditionally been underrepresented (certain minority groups, 

disabled, etc.). The reason we need these groups is that there is a labor 

shortage, and as digital and IoT roles grow, there will be a shortage of workers 

to do these jobs.

2. Development: Educating that worker base. This can be done at a variety of 

levels and means - vocational training, community college and university 

training, and continuing professional education. Development should target a 

variety of roles, from engineers to those that manufacture the digital 

solutions/products, to those that install and service them, as well as those that 

operate them. Some of this can be done by the military, as the use of IoT 

technologies are incorporated in government and military applications and 

facilities.

3. Placement. Once the workforce is trained or retrained, they need to be placed 

in industries across the economy, or in areas of the country with shortages of 

this labor (for example, rural areas, etc.). This includes new workers, as well as 

those reskilled from other industries. Note we had a recommendation in smart 

cities that talked about tuition forgiveness for those people that serve their time 

in these areas or industries where there is a need for skills. 
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4. Workforce Retention. We should have to retain workers who have been trained 

from leaving the industry or their roles. Some initiatives should be designed 

around addressing this issue.

When discussing IoT worker capabilities, there are many roles that are relevant, from 

designers to implementers to operations staff. For each role to be filled, the 

government can help foster collaboration about the necessary skills in each role and 

the knowledge needed to fulfill relevant tasks.

The federal government can help to develop targeted criteria and encourage 

expanded access to education and training opportunities. Agencies could help 

provide (or at least coordinate) means to assist learners through financial aid, 

scholarships, and online learning options. The U.S. can also encourage 

industry/academia partnerships as it has in other areas. This would help provide a 

focus on opportunities for existing workforce to adapt and better support digital 

transformation.

Enabling Recommendation ER4.1.1: The government promote continuing 

education, professional development, and vocational training for IoT 

integration in supply chain management.

Supported by Finding x.x

The recommendation to focus on education and workforce development, specifically 

geared toward the Internet of Things (IoT), is a response to the growing need for 

professionals adept in the design, implementation, and management of IoT systems 

within supply chain operations. This involves not just building knowledge in areas 

such as data science, analytics, data integration, and software development, but also 

developing a robust framework of continuing education, professional development, 

and vocational training. Such initiatives aim to equip businesses with a workforce 

capable of unlocking the full potential of IoT technologies.

The focus of these efforts should be a commitment to lifelong learning and 

continuous skills upgrade. This can be facilitated through various professional 

development opportunities such as workshops, online courses, and certification 

programs. These initiatives should be designed to help professionals stay current with 

the latest IoT trends and innovations, thereby promoting the adoption of new 

technologies in the supply chain sector. Vocational training programs, for instance, 

could provide hands-on experience in areas such as IoT device management, data 

analytics, and software development, thereby fostering technical proficiency. 
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Partnerships with industry stakeholders and technology providers are crucial. These 

partnerships can lead to internships, apprenticeships, and real-world projects, offering 

practical experience in IoT implementation. By focusing on these aspects of education 

and development, the government can create a pool of professionals who are not just 

knowledgeable but are also adaptable and up to date. This will ensure the workforce 

is well-equipped to navigate the complexities of IoT adoption, ultimately driving 

growth and competitiveness in the supply chain industry.

The justification for the recommendation to invest in education and workforce 

development in the context of IoT adoption in supply chain management lies in the 

need to prepare the workforce for the technological advancements and skills required 

in the rapidly evolving industry. The main reasons for this recommendation are:

• Addressing Skills Gap: The surge in IoT utilization in supply chain management 

will necessitate a workforce proficient in specialized areas such as data 

analytics, software development, and data integration. Investments in 

continuing education, professional development, and vocational training can 

bridge this gap, ensuring businesses have the skilled talent for effective IoT 

implementation.

• Enhancing Competitiveness: The competitiveness of the manufacturing sector 

hinges on a well-equipped workforce. Government investment in lifelong 

learning and skills development can bolster businesses' competitiveness, 

enabling them to maintain a robust global standing.

• Fostering Innovation: A workforce with deep-rooted IoT knowledge can spark 

innovation in supply chain management. Government-led educational and 

training programs can cultivate this innovative spirit, supporting the creation 

of avant-garde solutions.

• Supporting Digital Transformation: As the manufacturing sector undergoes 

digital transformation, there is a need to adapt operations to accommodate IoT 

and similar technologies. Education and workforce development investments 

can empower workers with the skills needed to support this transition, 

facilitating seamless integration of IoT in supply chains.

• Encouraging Job Creation: The integration of IoT in supply chain management 

can open new job avenues in areas like data analysis, software development, 

and cybersecurity. Government investment in education and workforce 

development can prepare workers for these opportunities, stimulating 

economic growth and job creation.

• Promoting Social Inclusion: Education and workforce development programs 

can enhance social inclusion, providing underrepresented groups with the 

necessary skills and training for the IoT-centric job market. This includes 

opportunities for professional development, vocational training, and 

continuous learning.
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• Ensuring Long-term Sustainability: As the manufacturing sector evolves, 

businesses need to adapt to emerging technologies and industry trends. 

Government investment in education and workforce development can support 

the sector's long-term sustainability, assisting businesses in their ongoing IoT 

adoption and integration efforts.

Implementation Considerations: Agencies should consider the following 

implementation considerations for investing in education and workforce 

development for supply chain IoT adoption including:

• Identifying Skill Requirements: Carry out an exhaustive analysis to identify the 

specific skills and expertise required to support IoT integration in supply chain 

management. This includes technical proficiencies in data analytics, software 

development, and data integration, and managerial competencies.

• Developing Targeted Curricula: Partner with training providers, industry 

stakeholders, and educational institutions to create curricula and training 

programs that cater to these identified skills. These programs should focus on 

professional development and vocational training, promoting lifelong learning 

and adaptability in the IoT domain.

• Expanding Access to Education and Training: Implement policies and 

programs that ensure extensive access to continuing education and training 

focused on IoT. This should involve financial assistance, scholarships, and online 

learning options, making these resources accessible to a broad audience, 

including underserved communities.

• Encouraging Industry-Academia Partnerships: Foster relationships between 

industry and educational institutions that facilitate real-world learning 

experiences, internships, and collaborative research projects. These initiatives 

can enhance practical skills development and provide valuable industry 

exposure.

• Focusing on Reskilling and Upskilling: Launch initiatives to reskill and upskill 

the existing workforce, ensuring they can adapt to the evolving demands of 

IoT-driven supply chain management. This reinforces the importance of 

continuous professional development and staying current with the latest 

trends and innovations.

• Promoting Vocational Training: Encourage interest in vocational training in the 

fields of science, technology, engineering, and mathematics (STEM), focusing 

on the development of IoT competencies within the existing workforce. This 

will lay the groundwork for future workforce development in the IoT field.

• Establishing Performance Metrics: Develop performance indicators and 

evaluation methods to assess the effectiveness of continuing education and 

professional development initiatives. This will enable data-driven 
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improvements, ensuring these programs remain relevant and effective in 

meeting the demands of the IoT-centric job market. 

Enabling Recommendation ER4.1.2: The government should develop 

educational initiatives that include IoT, targeting workforce development, 

and enhancing business, government, and consumer data privacy and 

trust.

Supported by Finding x.x

In response to the rapidly evolving landscape of the Internet of Things (IoT), the U.S. 

government has been recommended to develop targeted educational initiatives. 

These initiatives are not just focused on workforce development but also aim to 

enhance data privacy and trust among businesses, government entities, and 

consumers. The rationale behind this recommendation hinges on several key 

benefits: increasing the understanding and safe use of IoT technologies, cultivating a 

skilled workforce adept at navigating IoT privacy challenges, and bolstering trust and 

adoption of IoT devices and services across various sectors. 

To effectively implement these educational initiatives the government needs to 

undertake a comprehensive approach to effectively implement these educational 

initiatives. This includes defining the scope and content of the initiatives, identifying 

and reaching key target audiences like schools, universities, businesses, and the 

general public, and ensuring that the workforce development encompasses a broad 

range of personas, including manufacturers, implementors, service providers, and 

workers. 

Collaboration with educational institutions and industry leaders is vital, as is the need 

to ensure that the educational content remains relevant and practical. An essential 

aspect of this initiative is the regular update of these programs to align with ongoing 

technological advancements and evaluate their effectiveness through consistent 

assessments and feedback. In implementing these recommendations, the U.S. 

government should consider utilizing frameworks such as the National Cybersecurity 

Strategy Implementation Plan, specifically Initiative 4.6.1, which focuses on publishing 

and tracking a National Cyber Workforce and Education Strategy. This strategy could 

be a cornerstone in achieving the broader goals of enhancing understanding, skill 

development, and trust in IoT technologies.

Implementation considerations: Defining the scope and content of educational 

initiatives, identifying key target audiences (schools, universities, businesses, general 

public), collaborating with educational institutions and industry leaders, ensuring the 

relevancy and practicality of the educational content, regularly updating the 
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initiatives to keep pace with technological changes, and workforce development to 

encompass personas, including manufacturers, implementers, service providers, and 

workers. 

The government should facilitate policies and programs that support the key 

education and digital skills development across vocational schools, community 

colleges and four-year universities for the following sector-specific workforce areas: 

• Construction -The construction industry is behind the curve in digitalization. 

43% of U.S. civil engineers and contractors reported the use of digital tools and 

innovations, compared with 66% of non-U.S. counterparts. 43% of U.S. civil 

contractors had low digital capabilities, compared with only 23% of non-U.S. 

construction companies. In contrast, 45% of non-U.S. construction and 

engineering companies reported high digital capabilities, compared with just 

20% for U.S. companies.

• Insurance - Digital innovation is transforming the insurance industry. A 

shortage of digital skills and talent, however, is hindering the ability of the 

insurance companies to innovate and deliver new products and experiences, 

execute and operate new business models and to re-engineer existing 

processes and digitize operations.

• Retail - The retail industry is undergoing a long running technology 

transformation towards omni-channel retail. This is necessary for retailers to be 

relevant, operationally efficient, profitable and resilient. A lack of the relevant 

digital skills and workforce is hindering this transformation.

• Municipal and utility workforce - Manufacturing jobs are no longer low skilled 

jobs but require new skills. Automation will require people to work alongside 

robots and machines. A labor shortage and skills shortage will leave 2.4 million 

unfilled jobs between 2018-2028. This leads to a loss of $454 B of manufacturing 

value by 2028 and makes the U.S. less competitive in manufacturing.7
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Government Support to Facilitate Industry Adoption of IoT

Objective 5: The United States is recognized as an international leader in the 

innovation, deployment, and operation of IoT technology. Actions by U.S. 

government leaders set an example for private sector stakeholders and 

international partners.

Leverage Federal Grants And Programs To Improve IoT Technology Use

Key Recommendation KR5.1: The government should consider new 

financial models for sustaining and supporting programs when

considering IoT project feasibility.

Supported by Finding x.x

Grants offset acquisition and build, but many organizations lack financial means and 

resources to sustain IoT operations and maintenance. Because of this constraint, 

projects either shut down after funds run out or some entities are discouraged from 

applying. IoT requires additional levels of support and resources that buyers may not 

have accounted for – software licenses, data maintenance, data analysis, for example. 

IoT enables new business and operating models. Economic service models to assist 

could include extended funding for O&M for select applicants (i.e., rural, tribal, small 

towns, etc.), encourage regional cost sharing for multiple cities in a region to apply as 

one, and encourage innovative models (i.e., corporate, sponsorships).

Implementation considerations: There are types of models - 1) Extended Funding – 

extending funding for O&M for select applicants (rural, tribal, small towns, etc.). 2) 

Regional cost sharing – encourage multiple cities in a region to apply as one. 3) 

Innovative – encourage innovative models (corporate, sponsorships).

Enabling Recommendation ER5.1.1: The government should encourage 

other financial or funding models to help select adopting organizations 

sustain and support in evaluating IoT project feasibility.

Supported by Finding x.x

The federal government should consider models to help select adopting 

organizations sustain and support beyond the initial acquisition and building of new 

projects incorporating IoT technologies. While grants for projects help offset the initial 

cost of capital procurement, integration and development, the cost of operating the 

asset or system is left to the organization, municipality or agency. Some select 
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organizations have the resources, funding models, or mechanisms to find the 

resources to sustain the operation and maintenance of this asset or system. However, 

many other organizations, especially the smaller ones, or those in rural and tribal 

areas, that benefit from these technologies the most, do not have these mechanisms 

(budget, taxes, etc.), and may forgo these types of projects, or only operate the IoT 

applications short term until the funds run out. Similarly, current agency grant 

application evaluation criteria may screen out those that don’t meet the financial 

requirements for sustaining operations.

Implementation considerations: For existing grant programs, consider extending 

funding for operations from one to two years for applicants that meet specific criteria 

of those that can benefit from IoT but could not otherwise sustain it (rural areas, tribal 

areas, small cities and towns, etc.) Regional models: Incorporate models that 

encourage regional partnerships. For example, one small community may not have 

the means to sustain a small IoT application. But if multiple adjacent communities 

apply for a grant together, they may be able to leverage some economies of scale to 

purchase and set up the application but may be able to employ synergies and cost 

sharing to maintain the application together. Innovative partnerships: Incorporate 

criteria that encourage and reward innovative approaches to sustaining operations. 

For example, one city was able to sustain operations by implementing a “support a 

AQ node” and getting corporate sponsors in the business community to support the 

maintenance and operation of the network. 

Enabling Recommendation ER5.1.2: The government should consider 

“student loan forgiveness” programs in exchange for providing critical 

emerging technology (IoT, data science, cybersecurity, etc.) skills to 

municipalities and agencies.

Supported by Finding x.x

The federal government should consider “student loan forgiveness” programs in 

exchange for providing critical emerging technology (IoT, data science, cybersecurity, 

etc.) skills to municipalities and agencies. These programs, analogous to the National 

Health Science Corps, provide expertise to municipalities, agencies and utilities, 

especially smaller ones, that can help them to adopt, and accelerate the 

implementation and execution of these “smart solutions”.

Many cities lack the type of digital talent that is critically needed to implement and 

operate advanced technology. Moreover, many small cities and rural areas face an 

exodus (or “brain drain”) of workers. Cities, in general, often find it difficult to attract 

sufficient digital talent at a scale that will have an impact. Federal agencies can help 

cities to leverage a similar model to that used by the National Health Science Corps. 
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They can seek opportunities to partner with non-profit organizations (e.g., FUSE 

Corps) to find, attract, and hire talent. 

Enabling Recommendation ER5.1.3: The government should consider 

developing programs and grants to allow underserved and less developed 

communities

Supported by Finding x.x

Doing so would help improve national accessibility to benefits from the adoption of 

IoT technologies that are not currently available to all citizens and municipalities. 

Government grants and programs targeted towards these areas could spur private 

investment and growth in these areas, as well, further amplifying the economic and 

societal benefits that would result from such funding. 

Funding opportunities for these underserved and rural communities will create jobs 

and promote economic growth. As digital technologies are adopted in these areas, 

they will require skilled workers to develop, implement, and maintain these systems. 

Financial incentives can help stimulate this job growth and support the development 

of a skilled workforce in the IoT sector. to adopt smart transportation technologies.

Implementation Considerations: The government will need to identify appropriate 

tactics and methods, such as ADA-compliant EV Charging stations, adding EV-Ready 

language into building codes, opportunities for small- and disadvantaged businesses, 

or Department of Transportation (DOT) Grand challenges as programs/grants are 

developed. Clear eligibility criteria should be established to ensure that these 

grants/incentives are targeted only at these types of communities and areas. The 

federal government should establish a system for monitoring and evaluating the 

effectiveness of these grants and incentives.

Leading the Way for IoT Adoption in Agriculture

Key Recommendation KR5.2: The government should develop a 

comprehensive strategy for agricultural IoT.

Supported by Finding x.x

As IoT technologies continue to advance, their adoption in agriculture can 

significantly enhance productivity, resource efficiency, and environmental 

sustainability. However, without a cohesive national strategy, the potential benefits of 

agricultural IoT may be hindered by fragmented initiatives, limited interoperability, 

and a lack of clear direction. This strategy should be developed in collaboration with 
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stakeholders, such as farmers, technology providers, industry experts, and research 

institutions, to ensure broad consensus and commitment to its implementation.

The Federal government should identify and prioritize the most pressing challenges 

faced by the agricultural sector that can be addressed using IoT technologies, such as 

water management, pest control, and labor shortages. The government should 

develop specific goals, timelines, and milestones for the integration of IoT in 

agriculture, ensuring alignment with broader national objectives related to food 

security, environmental sustainability, and economic growth. This could be 

accomplished by establishing an interagency task force to oversee the development 

and implementation of the national strategy, involving relevant agencies such as the 

USDA, FCC, and DOE. 

The federal government should consider programs to help growers and producers 

adopt IoT technologies. This should include subsidies around connectivity, sensors, 

and digital applications. The programs could be similar to other subsidies that the 

USDA has for farmers around agricultural inputs or climate-smart agriculture. The use 

of IoT in agriculture will benefit all stakeholders, including the farmer, the 

policymakers, the agricultural companies, and the consumer.

The upfront cost of IoT typically limits the adoption of data-driven agriculture, and the 

farmers who may have the most need may be the ones least likely to take advantage 

of digital technology. Federal subsidies can help scale the technology, which will drive 

down costs for all, and could help marginalized farmers and smallholder farmers who 

might need more help to leverage technology.

Developing an approach to IoT subsidization could involve a public / private / 

academic partnership and leveraging the knowledge and capabilities of Agricultural 

Extension centers. Particular attention should be paid to defining approaches that will 

enable marginalized and smallholder farmers to leverage available subsidies to 

deploy and benefit from IoT technology. 

Enabling Recommendation ER5.2.1: The government should consider fully 

funding the deployment of a “farm of the future” setup in every land grant 

university nationwide. This nationwide test-farm IoT network should span 

different forms of agriculture, including, but not limited to broadacre, 

horticulture, livestock, and aquaculture.

Supported by Finding x.x

The proposed initiative advocates for the federal government to allocate sufficient 

funding to implement a "farm of the future" setup in all land grant universities across 
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the United States, providing a showcase for farmers in the region on how to collect 

and analyze data from their farms. 

The data collected by the IoT network could be used to develop and refine machine 

learning algorithms, which could help farmers predict future crop yields and identify 

potential issues before they occur. (Note: That data might also be housed and shared 

through data repositories described in other recommendations.)

The nationwide "farm of the future" IoT network would enable universities to share 

data and insights with each other more easily, fostering a collaborative approach to 

agriculture. 

The implementation of a nationwide IoT network in land grant universities could help 

to advance research and development in agriculture, leading to the creation of new 

technologies and practices that could benefit farmers and consumers alike. 

It is difficult to specify what IoT technologies should be acceptable to be used. Some 

concrete and specific IoT applications should be defined for inclusion in the project 

and funding requirements, based on project types. 

Implementation Considerations: “Farm of the Future” efforts should look to assist in 

determining what IoT technologies should be acceptable for use. Some concrete and 

specific IT applications should be defined for inclusion in the project and funding 

requirements, based on project types. This may require coordination with other 

federal agencies in alignment with their objectives. Different land grant universities 

might pose different challenges with respect to implementation, including 

connectivity, tech readiness, etc. It is important to include every university, including 

the HBCUs. 

Enabling Recommendation ER5.2.3: The government should provide 

overarching regulatory guidance for the drone industry. The Federal 

Government should also provide funding for the drone industry for 

additional research in order that existing technical obstacles can be 

overcome.

Supported by Finding x.x

There are conflicting regulations that govern drones for recreational pilots versus 

those that govern drones for commercial pilots. The regulations that govern drones 

for commercial pilots are put forth by the Federal Aviation Administration (FAA) as 

they regulate that section of the airspace. Sometimes these regulations are 
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mistakenly applied to recreational pilots. In some jurisdictions there is uncertainty 

over who regulates the airspace for recreational pilots (FAA versus Local Police).

In addition, there are commercial drone pilots that fly large aircraft in sections of the 

airspace that fall under Advanced Air Mobility (AAM) jurisdiction. Another issue facing 

the drone industry is Remote ID — a requirement for a drone to have an internal signal 

broadcasting the drone’s location, latitude, longitude and heading. Not all drones 

currently meet this requirement. 

Implementation Considerations: It will be necessary to involve all stakeholders: 

drone equipment manufacturers, communications providers, among others need to 

be involved. This should be accompanied by expanding access to education and 

training: particularly on safety aspects related to drones.

The adoption of drone technology can have substantial impacts on the nation's key 

sectors. In agriculture, for instance, drones equipped with advanced sensors can help 

in efficient farm scouting, pinpointing areas of pest infestations, disease, or poor 

irrigation. This not only enhances productivity but also promotes precision farming by 

reducing the excessive use of chemicals. For the energy sector, drones can monitor 

electric grids and detect faults or required maintenance, helping to prevent power 

outages and ensuring a stable power supply. Similarly, drones can be utilized for 

environmental monitoring of forests, aiding in early detection of wildfires and thus 

mitigating their devastating effects. Drones can also be actuated to perform tasks 

such as spraying pesticides or fertilizers in farming, reducing human exposure to 

harmful chemicals, and ensuring that the process is accomplished with greater 

precision and less waste.

The Internet of Things (IoT) is instrumental in accelerating the adoption of drone 

technology, including the use of drones in Non-Line-of-Sight (NLOS) operations. IoT 

facilitates seamless communication and data exchange over the Internet, enabling 

real-time data collection and analysis, remote control of drone operations, and 

automation of tasks. This is particularly beneficial for NLOS drone operations, which 

require sophisticated data communication and handling capabilities. Drones 

operating beyond visual line of sight can cover larger areas and perform tasks in 

remote or inaccessible locations, expanding their utility in sectors such as agriculture, 

energy, and environmental monitoring. However, leveraging the potential of NLOS 

drone operations hinges on the establishment of appropriate regulatory guidance for 

IoT in the drone industry. Such regulations can address critical aspects such as data 

security and privacy, airspace usage, safety, and accountability for NLOS operations. 

By providing clarity and assurance, these regulations can stimulate innovation and 

investment in drone technology, contributing significantly to the economy and 

society at large.
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Enabling Recommendation ER5.2.4: The government should support and 

promote industry and SDO efforts to address interoperability of 

agricultural systems and machinery. 

Supported by Finding x.x

Farms have a variety of equipment and machinery from different manufacturers that 

can’t communicate or exchange data with each other, each with its own data formats 

and languages. The agriculture industry model is to develop s/w and devices in 

proprietary formats.1 This lack of interoperability hinders data sharing, automation of 

processes, and timely diagnosis and analysis of problems to create positive outcomes. 

In addition, costly manual labor is required to extract the data for use. 

 

Implementation considerations 

There are a variety of SDOs and industry associations that are addressing small parts 

of this much broader problem. However, broader efforts involving the major 

equipment manufacturers are needed. 

Enabling Recommendation ER5.2.5: The government should facilitate small 

farm/ranch adoption of IoT technologies. 

Supported by Finding x.x

Small farms (< $350,000 GCFI)2 are 90% of all U.S. farms (~1.8 million farms), own 49% 

of farmland, but represent 20% of production. They operate with <10% margins. 

Because of their small scale and low margins, they are cash flow constrained and do 

not have the capability to buy IoT or smart equipment, even if they want to. 

 

Implementation considerations: 

• Offer grants and subsidies for purchase. Since these small farms operate on low 

margins, they have limited upfront cash available for investment is a critical 

barrier to adoption. 

• Tax credits offer another way to incentivize purchase but may not be a viable 

option for those small farms that do not have the upfront cash to purchase and 

use. 

• Use of Cooperative Extension Offices and resources for IoT data analytics and 

other technical support. In order to ensure that IoT is being used, additional 

support (beyond what the IoT vendor provides) is necessary to help the 
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agriculture producers get the value out of the data collected so they can 

optimize outcomes. 

• Need to define and specify what subset of IoT devices and solutions would be 

addressed by this. 

Enabling Recommendation ER5.2.6: The government should support 

enactment of federal “right to repair” legislation to address the inability of 

agricultural producers to service their smart equipment. 

Supported by Finding x.x

Smart equipment cannot be fixed by farmers. In many cases, it required servicing by 

the equipment dealer technicians. These repairs are expensive and may take a long 

time to get fixed. These may occur at sensitive times for farmers who can’t afford the 

wait, such as during harvest season. Today, farmers are getting around this by 

purchasing “hacked” software from Eastern Europe or buying older non-smart

equipment that they can maintain and repair themselves.3

 

 

Implementation considerations 

• Current legislation has been introduced - the Agricultural Right to Repair Act4

- review to ensure that precision agriculture and IoT needs has been addressed 

in legislation
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Leading the Way for IoT Adoption Through Smart Cities

Key Recommendation KR5.3: The government should implement specific 

actions to further promote IoT adoption through smart cities. 

Supported by Finding x.x

[Text needed]

Enabling Recommendation ER5.3.1: The government should facilitate and 

support the development and use of smart city and sustainable 

infrastructure reference models.

Supported by Finding x.x

The federal government should facilitate and support the development and use of 

smart city and sustainable infrastructure reference models that capture and 

document the ecosystem.

Smart cities are complex ecosystems of communities, neighborhoods, districts, 

buildings, other cities, utilities, and businesses that co-exist, collaborate occasionally 

and interoperate with each other. A framework is needed to help municipalities, 

solution vendors and smart city integrators build smart cities that are interoperable, 

secure, scalable, resilient and relevant.

The reference models and framework capture the various components of the 

ecosystem and provide a blueprint for design and planning, collaboration, 

coordination and communication in smart city efforts, sharing and economies of 

scale. These reference models include technical and operations frameworks and 

architectures, operational concepts, and draft requirements and reference standards. 

The reference models serve as a template that planners can use to plan, design and 

build their smart city projects, and if followed, provides a path for interoperability, 

scalability, integration and security. Furthermore, these models incorporate best 

practices and facilitate collaboration between various stakeholders, accelerate 

adoption and scaling, and are replicable. A broader reference model/architecture 

helps to identify use cases, potential areas of collaboration between entities, as well as 

identify areas of “sharing” and economies of scale. 

Justification 

• Cities are complex ecosystems of communities, systems and users that co-exist, 

collaborate occasionally and interoperate with each other. However, many IoT 
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projects are planned as individual projects by different city agencies with 

limited consideration of other agencies and smart city systems. This results in 

redundancy and inefficiencies as each project uses its own separate 

infrastructure instead of sharing common infrastructure and processes.

• The siloed approach leads to interoperability issues, and hinder disparate 

applications wish to communicate and share data. This results in significant 

efforts and resources to integrate, maintain and operate these systems. 

• There is not a common approach, model and framework that the various city 

agencies and vendors plan to and build that enables the vision and intentions 

of a smart city. 

Implementation considerations

• A 2018 effort, led by NIST in collaboration with a variety of industry partners, 

have created an initial start of a V1.0 of a smart city framework 

https://pages.nist.gov/smartcitiesarchitecture/). This effort lead to a variety of 

concepts, including the principal points of interoperability that takes into 

account the various needs around interoperability. This effort should continue 

that initial started effort.

• The NIST GCTC has already established a structure and model to create, engage 

and support industry/academia/government partnerships. This effort should 

consider inclusion of public entities such as counties, states, and other regional 

agencies and utilities. The effort should consider leveraging the GCTC approach 

to bring industry together to define this reference model and framework.

• There is not a one size fits all “reference model and architecture”. There is one 

for small cities, large cities, as well as “smart regions”, utilities, buildings, etc. Key 

participants in developing the reference model include government (states), 

federal, industry (and industry and standards bodies), and academia. There are 

various efforts around models and standards. 

• Consider projects that are funded using federal money to incorporate the use 

of these reference models. 

Enabling Recommendation ER5.3.2: The government should consider the 

development of Smart City and Sustainability Extension Partnerships 

(SCSEP).

Supported by Finding x.x

IoT can bring great economic and societal benefits to our cities, but specific smart city 

and sustainable infrastructure expertise in industry is limited, unevenly distributed, 

and fragmented. Some cities and agencies also lack the tools and resources, and even 

smaller cities and agencies may be even more constrained. Municipalities and 
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agencies may not have the budget, the empowerment, or the ability to engage the 

necessary resources. 

A different way to engage these resources is needed. The public procurement 

processes to engage private sector resources are burdensome. A SCSEP similar to 

existing partnerships (e.g., MEP, USDA) would be a worthwhile investment, and would 

provide an improved model over the current public procurement process to engage 

private sector resources.

SCSEP should be put in place and operational to support sustainable infrastructure 

projects funded through the Bipartisan Infrastructure Law (BIL) and the Inflation 

Reduction Act (IRA). The role of states should be defined. In particular, some BIL and 

IRA funding may be given to states to manage and allocate. Consideration should be 

given as to whether some of these activities can be performed through the existing 

extension offices and infrastructure, or through partnerships with regional 

consortiums or states.

Implementation Considerations: Smart cities, sustainable infrastructure and IoT are 

broad in scope and discipline. A SCSEP should be a multidisciplinary center with 

spanning expertise (technical, operations, cybersecurity, etc.). The expertise lies across 

a variety of areas and could be implemented through partnerships with public (state, 

local) agencies, industry, and universities. There are a small number of regional “smart 

city” type consortiums across the country. Consider establishing partnerships or 

collaboration with these consortiums to support or enable these capabilities. For 

example, the USDA agriculture extension offices and the U.S. Department of 

Commerce manufacturing extension partnerships model as starting points. They 

have built infrastructure and processes. In some rural areas, perhaps this is how these 

capabilities of the SCSEP should be delivered.
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Enabling Recommendation ER5.3.3: The government should facilitate 

opportunities for adoption and equity of benefits of IoT and smart city 

technologies for local governments (cities, counties), regional entities 

(water districts, sanitation districts, air quality districts, etc.) and utility 

companies.

Supported by Finding x.x

The government should facilitate opportunities for adoption and equity of benefits of 

IoT and smart city technologies for local governments (e.g., cities, counties), regional 

entities (e.g., water districts, sanitation districts, air quality districts, etc.) and utility 

companies. This may include: 

• Funding regional or state programs that support municipalities and local 

governments in strategy and roadmap development and integration of smart 

city technologies into city vision, infrastructure and operations. 

• Project grants for smart city and related innovations pilot projects and 

deployment projects 

• Consideration and specification of IoT applications into the design, 

construction and operation of federally funded infrastructure projects (e.g.,

highway projects, street improvements). 

Justification 

IoT and smart city technologies bring a variety of beneficial outcomes to communities, 

from economic vitality of local economies, improved quality of life, reduction in crime 

and increased mobility, and more responsive government services. However, not 

everyone and every community is able to share in the outcomes from these 

technologies. Some communities lack the connectivity, broadband and digital 

infrastructure required, while others lack the skilled workforce and resources to 

implement and operate these technologies. Still others lack access to funds, or the 

ability to access funds to procure these technologies.

As a result, there are inequities in access and benefits between large and small 

municipalities and agencies, urban, suburban and rural communities, and wealthy 

and socio/demographically underserved communities.

Implementation considerations

• Integrate IoT and smart cities/communities initiatives into existing federal 

programs and funding infrastructure.

• Leverage existing programs targeting socio/demographically underserved 

communities,
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• Target smart city grants towards those underserved communities that have 

already received broadband grants to build on new connectivity infrastructure 

• Support industry and other existing partner efforts to increase the awareness 

of the benefits of these technologies and applications within those targeted 

communities

Enabling Recommendation ER5.3.3: The government should facilitate 

smart community opportunities and adoption of IoT for those rural 

communities that have broadband infrastructure, have received 

broadband infrastructure funding or have completed broadband 

infrastructure build-outs. 

Supported by Finding x.x

The government should facilitate smart community opportunities and adoption of IoT 

for rural communities. This may include: 

• Coordination with federal agencies (USDA, NTIA, EPA, DOT, etc.) to drive 

community awareness of IoT opportunities, and support programs that 

encourage industry participation 

• Offering project grants for community related IoT projects and deployment 

projects (e.g. environmental monitoring, etc.) 

• Consideration and specification of IoT applications into the design, 

construction and operation of federally funded rural infrastructure projects (e.g. 

highway projects, street improvements, energy transmission lines, etc.) 

Rural communities lack many of the same resources, services and amenities that 

residents in urban areas benefit from. The lack of infrastructure, low population 

densities, private sector investment and other factors contribute to the urban/rural 

divide. For example, many rural areas are considered medical deserts with limited 

number of healthcare providers and facilities. As a result, healthcare access inequities 

exist. Telehealth and home healthcare monitoring are IoT-enabled services that can 

alleviate some of these inequities.
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Enabling Recommendation ER5.3.4: The government should support and 

promote industry and SDO efforts to address interoperability of smart 

cities (including smart buildings, energy and utilities, traffic) 

Supported by Finding x.x

Interoperability challenges are a major barrier to maximizing the value of IoT and 

smart city technologies. Disparate IoT devices and smart city systems have limited to 

no ability to communicate with each other and other city systems. This limits the 

ability of the city to monitor conditions, automate operations, respond quickly, 

effectively and efficiently. 

Enabling Recommendation ER5.3.5: The government should facilitate small 

to medium city adoption of smart city technologies. 

Supported by Finding x.x

Considerations include:

• Develop smart city grants targeted for smaller communities and rural 

communities [linkage to existing recommendation] 

• Develop smart city grants for communities that receive broadband 

infrastructure funding (BIL, USDA, etc.), to encourage them to build on their 

infrastructure investments 

• Consider program grants that allow these communities to sustain the 

operation and maintenance of smart city technologies beyond the initial 

project funding (for initial acquisition, installation and operation). [linkage to 

existing recommendation in smart cities/sustainable infrastructure] 

• Consider creating smart city innovation extension partnerships (modeled after 

MEP and agriculture extension offices) to provide the smaller cities with the 

technical and innovation expertise, resources and capabilities to design, 

operate and innovate with smart city technologies [linkage to existing 

recommendation in smart cities] 

• Facilitate workforce development to support innovation, IoT and digital 

technologies in smaller cities (including municipalities, regional entities, and 

utilities) 

There are 1300 cities that have less than 250,000 people. These cities lack the funding, 

expertise and resources to implement, operate and maintain smart city technologies. 

At the same time, these smaller cities have needs that are different from their larger 

city counterparts and may require grants that are more aligned to their needs. 
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Enabling Recommendation ER5.3.6: The government should facilitate 

equity in realization of smart city benefits.

Supported by Finding x.x

This may include: 

• Smart city project grants for underserved and rural communities, including 

those applications where underserved communities are disproportionately 

impacted (e.g. environmental monitoring, healthcare, public safety, etc.) 

• Increase access to broadband services and affordability 

• Workforce development opportunities for residents of underserved and rural 

communities for the new IoT and digital jobs to be created 

Benefits of IoT and smart city technologies are not available to all members of a 

community. Socioeconomically challenged and rural communities may not have the 

broadband infrastructure, or have limited resources to implement and operate smart 

city technologies. The new jobs created by IoT, smart cities and digital transformation 

require skills and education that members of underserved communities may not be 

able to develop. Some services enabled by these technologies require smart phones 

and Internet service to access, which some community members may not have, while 

others are offered in ways that cannot be accessed by residents due to language 

barriers, digital literacy skills, etc.

Leading the Way for IoT Adoption for Public Safety

Key Recommendation KR5.4: The government should implement specific 

actions to promote IoT adoption that will improve public safety. 

Supported by Finding x.x

Enabling Recommendation KR5.4.1: The government should create a 

stockpile of public safety IoT devices that is available for immediate access.

Supported by Finding x.x

[Note: The Board recommended this for removal. To be discussed at the January 

meeting.]

The federal government should create a program that enables local communities to 

purchase IoT systems or IoT enabled systems for public safety applications. This 
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includes systems that support law enforcement, fire, emergency management 

services, and public safety access points. 

Justification

• Communities have very limited ability to purchase IoT equipment for public 

safety on their own, with supplemental funding from external sources

• The adoption of IoT for public safety is limited for a variety of reasons, including 

a lack of awareness, lack of funding, interoperability challenges, privacy 

concerns and community support.

• Each community has its own unique priorities, needs and systems that 

translate to different types of IoT systems and applications that best serves their 

community

Implementation considerations

• The IoT devices, systems and applications should be interoperable with the 

FirstNet network. This at least drives us toward some sort of connectivity and 

perhaps functional interoperability.

• The grant should specify the need for the development, in collaboration with 

the community, some privacy and usage policy for those devices that may 

collect personal data. 

• The grant should specify that devices should support industry standards, 

including any open standards that may be applicable

• The grant should include funding for the installation and integration, as 

needed, of the IoT devices into existing operations and processes. In addition, 

the grant should include some initial training of users. 

• The appropriate federal agencies (e.g. DHS, FEMA?) will need to work with 

communities and the FirstNet Authority to identify an initial IoT list (e.g. drones, 

flood gauges, etc.) and guidance of what IoT applications this grant would help 

procure. 

• The grant should support or integrate into, as relevant and applicable, next gen 

911 systems

• There may already be existing grant funding vehicles for the procurement of 

technologies for public safety (including law enforcement, community 

resilience, disaster response, etc.). If so, these funding vehicles should be 

updated to support this.

• Consideration should be given for prioritizing certain applications for certain 

communities. For example, in communities prone to wildfires, the grant should 

prioritize the procurement of IoT systems that detect wildfires, support 

emergency response and community evacuations.
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Enabling Recommendation KR5.4.2: For public safety and smart city projects 

supported by federal grants that utilize IoT technologies (such as cameras, 

plate readers, and other applications that may be used to identify people), the 

grantor agencies should include a provision specifying the need for the 

awardees to develop privacy and data usage policies in collaboration with the 

communities that they serve as part of the deployment. 

Supported by Finding x.x

IoT sensors and camera systems provide high value in addressing public safety issues. 

This includes monitoring events and preventing incidents, spotting and informing on 

hazards, illegal and dangerous activities, and identifying suspects and persons of 

interest. However, concerns about unauthorized and inappropriate data collection, 

misuse and misinterpretation of the data collected, and lack of governance and 

accountability, have led communities to ban or limit the use of these IoT systems. This 

leads to a loss of beneficial outcomes that would have otherwise been realized by the 

community.

A lack of awareness and understanding of these technologies is a major cause of these 

concerns. The community is often unaware of how these technologies work, its 

limitations and capabilities, how the data is used, and the role of policies and 

processes in ensuring and maintaining proper usage. Furthermore, the communities 

that these technologies are deployed in are often not involved nor consulted in 

defining how these systems are used. As a result, many of the systems operate in a 

way that is not always in alignment with community concerns, leading to poor 

outcomes and an overall distrust in the technology.

Implementation considerations: 

Any language should point to external organizations (e.g. (such as the Major Cities 

Chiefs Association) as well as privacy advocacy organizations that grant awardees can 

go to in order to define and specify resources, best practices, training and templates

that grantees can use to draft and enact policies. Grantees may not know what is 

current or what is available.
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Enabling Recommendation KR5.4.3: Federal RFPs/RFIs that support public 

safety applications should include a requirement for bidders to consider 

how IoT can be incorporated into it, as well as to include an IoT user 

adoption and utilization plan as part of the evaluation process.

The federal government funds a variety of large-scale programs that support public 

safety IoT applications. However, one major challenge is that when the program or 

platform is built or made available for use, there is a lack of user adoption and 

utilization. One reason for this is low user awareness that this program or platform 

exists. Another reason is that the program (and technology) may have been designed 

and developed in such a way that it is too expensive for users. For example, the 

program may be designed for expensive proprietary applications or devices, or it may 

have limited interoperability to support low cost devices based on industry or open 

standards. This limits what IoT devices this program can support.

In order to fully leverage and justify the investment in these programs, potential 

bidders will need to discuss how they will market this program to its customers (public 

safety agencies, cities, etc), and how they have designed and developed it in a way 

that makes economic sense for its potential users to be able to use, grow its usage, 

and support future applications.

Implementation considerations:

Include provisions or requirements in the RFP/RFI to include how and where IoT can 

be incorporated, as well as a market and user adoption/growth plan

Enabling Recommendation KR5.4.4: The federal government should create 

a program that enables local communities to purchase IoT systems or IoT 

enabled systems for public safety applications. This includes systems that 

support law enforcement, fire, emergency management services, and 

public safety access points.

Communities have very limited ability to purchase IoT equipment for public safety on 

their own, with supplemental funding from external sources

The adoption of IoT for public safety is limited for a variety of reasons, including a lack 

of awareness, lack of funding, interoperability challenges, privacy concerns and 

community support.

Each community has its own unique priorities, needs and systems that translate to 

different types of IoT systems and applications that best serves their community
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Implementation considerations: 

The IoT devices, systems and applications should be interoperable with the FirstNet 

network. This at least drives us toward some sort of connectivity and perhaps 

functional interoperability.

The grant should specify the need for the development, in collaboration with the 

community, some privacy and usage policy for those devices that may collect 

personal data. 

The grant should specify that devices should support industry standards, including 

any open standards that may be applicable 

The grant should include funding for the installation and integration, as needed, of 

the IoT devices into existing operations and processes. In addition, the grant should 

include some initial training of users.

The appropriate federal agencies (e.g. DHS, FEMA?) will need to work with 

communities and the FirstNet Authority to identify an initial IoT list (e.g. drones, flood 

gauges, etc.) and guidance of what IoT applications this grant would help procure. 

The grant should support or integrate into, as relevant and applicable, next gen 911 

systems

There may already be existing grant funding vehicles for the procurement of 

technologies for public safety (including law enforcement, community resilience, 

disaster response, etc.). If so, these funding vehicles should be updated to support this.

Consideration should be given for prioritizing certain applications for certain 

communities. For example, in communities prone to wildfires, the grant should 

prioritize the procurement of IoT systems that detect wildfires, support emergency 

response and community evacuations.

Leading the Way for IoT Adoption for Health Care

Key Recommendation KR5.5: The government should implement specific 

actions to promote IoT adoption in the health care industry.

Supported by Finding x.x

[Still undergoing significant revision]
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Enabling Recommendation ER5.5.1: The government should promote IoMT 

as an enterprise priority, including to healthcare facilities’ leadership 

teams.

Supported by Finding x.x

IoMT should be equivalent in priority for all healthcare stakeholders as is IT 

infrastructure, cybersecurity posture, or applications. IoMTs monitor, detect, inform, 

and deliver therapies to patients, therefore, they deserve just as much attention and 

call out as cloud services, for example. Currently IoMTs are often ignored by healthcare 

IT organizations, as the responsibility to make decisions and/or purchase the devices 

is owned by the biomedical engineering department. IoMTs may not undergo strict 

infrastructure, privacy, and security guidelines as to large capital equipment 

investments such as MRI scanners.

Enabling Recommendation ER5.5.2: Facilitate cybersecurity in IoT in smart 

medical devices and equipment, including wearables, in-home devices, 

community IoMT systems, and a continuum of care.

Supported by Finding x.x

[Still undergoing significant revision]

• Facilitate workforce development programs to increase pool of IoT 

cybersecurity trained resources for healthcare industry on both the solution 

provider side and care provider (buyer) side 

• Consider development of programs, resources and incentives to help 

healthcare providers migrate away from those vulnerable legacy equipment 

and devices that cannot be patched, or upgradeable, or were not subject to 

compliance with section 524B of the Federal Food, Drug, and Cosmetic Act 

(FD&C Act)

• Develop a plan to audit, inspect and update healthcare and medical IoT 

devices, and the networks they operate in used in federally owned or funded 

health facilities (e.g., VA medical facilities, military medical facilities, etc.). 

Replace those legacy devices and equipment that cannot be patched or 

upgradeable or not subject to compliance with section 524B of the Federal 

Food, Drug, and Cosmetic Act (FD&C Act). Verify devices and systems, and 

practices meet IoT cybersecurity guidance and best practices. 

Justification: 

Healthcare and medical IoT devices and systems are susceptible to cyberattacks. 

These cyberattacks not only expose sensitive and personal health data and 

information, but they could lead to disruption to the operation of the devices and 

systems, leading to potential injury and loss of life. Areas of healthcare and medical 
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device IoT cybersecurity concerns include:

• Vast attack surface due to the interconnected nature of IoT and IoMT devices. 

Each connected device represents a potential entry point for malicious actors 

seeking to exploit vulnerabilities.

• Protecting data in transit and at rest is of concern because the data generated 

by IoT and IoMT devices in healthcare include sensitive patient information. 

Encryption is critical to preventing unauthorized access.

• Unauthorized access to healthcare data can have severe consequences, 

ranging from identity theft to compromised patient care. Robust 

authentication and access control mechanisms is essential to restrict data 

access to authorized personnel only.

• Patching millions of IoT and IoMT devices is logistically and operationally 

challenging. These devices often have a longer life cycle than traditional IT 

devices, and some lack the capability for regular software updates. Not all 

device and system owners apply patches and firmware updates. 

• Legacy systems and devices that cannot be patched or updated with the 

latest software to address known vulnerabilities

• Compliance with regulatory frameworks (e.g. HIPAA) can be challenging due 

to the dynamic and evolving nature of IoT and IoMT technologies.

Securing endpoints (devices) and gateways against unauthorized access and 

breaches is critical as they act as crucial points in the data transmission process for 

IoT and IoMT devices. 

Enabling Recommendation ER5.5.3: Facilitate and support the use and 

adoption of healthcare IoT in rural communities 

Supported by Finding x.x

[Still undergoing significant revision]

• Facilitate grants to drive healthcare IoT adoption among healthcare providers 

in those communities that have received broadband grants to build on new 

connectivity infrastructure

• Coordination with federal agencies to drive physician and patient awareness 

of IoT in healthcare for treatment

Justification

Rural communities lack many of the same resources, services and amenities that 

residents in urban areas benefit from. Many rural areas are considered medical 

deserts with limited number of healthcare providers and facilities. In addition, 

residents in rural areas tend to be sicker than their urban counterparts, as well as 
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older and more likely to suffer from chronic conditions. In addition, many have 

limited transit options to go see a doctor on a regular basis.

As a result, healthcare access inequities exist. Telehealth, home healthcare 

monitoring and consumer health tracking are IoT-enabled services that can alleviate 

some of these inequities by providing access to healthcare and improving their 

health outcomes. 

Implementation considerations

• Code IoT-enabled services in Medicare to support senior population in rural 

areas 

• Facilitate support from private payers (insurance companies) 

• Focus on chronic disease management

Enabling Recommendation ER5.5.4: Facilitate the adoption of AI in IoT in 

healthcare through improved AI research, development and workforce 

improvement.

Supported by Finding x.x

• Support research in the development of trustworthy AI algorithms and tools, 

including AI explainability

• Facilitate the development of IoT data usage and privacy policies that support 

the development of AI algorithms [linkage with Debbie recommendation]

• Support workforce development efforts to increase the pool of workers 

trained in data analytics and AI 

While AI can help automate the analysis of massive amounts of IoMT data, and other 

data collected from health records, its ability to create explainable, beneficial and 

personalized outcomes specific to the patient that are clinically appropriate, reliable 

and accurate is a major challenge. 

AI algorithms review and analyze data, and make recommendations and in cases 

requiring autonomous operations, take action. Diagnosing people and identifying 

treatments for people is complex. Diseases such as cancer are complex, and there is 

still much to be learned. Furthermore, each person has a different reaction to 

treatments and what works for one person may not work for another. AI generated 

recommendations may yield treatment recommendations that lead to adverse 

outcomes, including injury and death. There are a variety of reasons AI may lead to 

negative or unintended outcomes, including data that may be outdated, contains 

bias, or incomplete. The source of the data may be unknown for privacy reasons. While 

the AI algorithms have been trained on this data, the reasons it led to a specific 
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recommendation may not be explainable and transparent. This leads to a loss of 

confidence in the AI’s ability to analyze the data accurately and reliably.

Enabling Recommendation ER5.5.5: The government should enact HIPAAlike protection for users’ medical data in mobile applications and IoT 

devices. 

Supported by Finding x.x

Many consumer-grade IoT devices and mobile apps collect users’ sensitive medical 

data. Consumers tend to believe that this data is protected similarly to medical data 

in a healthcare facility, but it is not. 

Consider medical data as a category for defined data protections. It should be noted 

that this Recommendation represents a major change. Many organizations have IoT 

products but no HIPAA experience. While the direction should be clear, the impact 

should be understood in advance through study, and the transition period adequate 

to allow manufacturers to adapt without unnecessary impact. 

The desired goal is to extend HIPAA protections to these classes of devices and mobile 

apps or enact a similar type of protection. 

Sustainability / Environmental Monitoring

Key Recommendation KR5.6: The government should implement specific 

actions to promote IoT adoption that will improve sustainability and 

environmental monitoring. 

Supported by Finding x.x

[Text needed]

Enabling Recommendation ER5.6.1.: The government should support 

development of IoT environmental data repositories to better enable open

and available data.

Supported by Finding x.x

Promoting the open availability of data would support research, improve 

transparency, and encourage proactive improvement by industry participants. As 

described in other recommendations throughout this report, improved 
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interoperability and competitiveness will help benefit all IoT adopters, and an open 

model for shared and consistent data will help take strides toward those objectives. 

A great deal of IoT environmental data (e.g., air quality, or AQ, measurements, water 

levels) is collected by a variety of federal agencies. This data would be useful to a lot of 

organizations, communities, universities and other researchers. For example, 

historical AQ data for a particular area of a city could be used by public health 

researchers to identify patterns among respiratory health diseases. For maximum use, 

a number of barriers that need to be overcome, including normalizing the data. 

Different sensors may have different formats, and so one reading in one brand may 

not correlate with the same reading on another brand, etc.

Some implementation considerations include:

• Environmental data that is collected by a variety of federal, state and municipal 

organizations. The data repositories should support the data types collected 

and the needs of the various organizations in mind.

• Environmental monitoring projects funded by federal grants should include 

provisions supporting the sharing of the collected data to this open repository.

• Third-party organizations should manage any open repositories.

• Data repository should aim for consistency in data reporting, but also focus on 

direct raw measurements from IoT devices. 

Enabling Recommendation ER5.6.2: The government should facilitate and 

support the research, development and deployment of low cost Air Quality 

sensors.

Supported by Finding x.x

The Board observed that there is a need to shift from expensive (i.e., highly sensitive 

regulatory grade) monitors that limit deployment by organizations and 

municipalities. Furthermore, there is a widespread interest in participatory science 

(aka citizen science) where communities or individuals are actively engaging in air 

quality monitoring. While such monitors are vital for particular purposes, large scale 

deployment of these types of monitoring equipment would be expensive and difficult.

Low-cost air quality sensors enable widespread monitoring for numerous applications 

and by multiple types of users.

Encouraging development and implementation of local, scalable air quality 

monitoring would support a variety of use cases, including:

• Increasing public awareness of air quality conditions;
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• Informing environment and public policy, including through real time testing 

and demonstration of policy impacts; 

• Environmental justice work;

• Supplementing regulatory grade sensing with IoT commercial sensors;

• Public health research;

• Construction site emissions monitoring; and,

• Rapid or emergency air quality monitoring for particular circumstances.

Currently, regulatory monitoring is often limited to a few pollutants; the government 

can encourage expanded coverage of other emerging chemicals of concern 

(including greenhouse gasses) in monitoring and sensing systems.

Agencies should encourage automated and consistent measurement and can 

facilitate research in low-cost sensing technologies for criterial regulated air

pollutants. Additionally, research should be supported for other emerging chemical 

of concern.

IoT sensing allows for the effortless collection of data from multiple devices and 

technical innovation in IoT has emerged in research communities worldwide, which 

together provide new opportunities for low-cost, high resolution, environmental 

monitoring. There are numerous applications where these sensors can help the public 

immediately take steps to protect their health (e.g., in the case of wildfire or smoke 

events) or provide communities with evidence that there are air quality concerns in 

their area which they can use to encourage action for improvements. However, wider 

implementation of such devices in the United States will require the approval and 

encouragement of the federal government if to be used for regulatory purposes.

• Regulatory grade sensors are expensive, limiting the number that can be 

deployed. Their purpose is specific to looking at broad air quality of an area and 

compare against EPA levels to protect health and welfare (epidemiological 

reasons). This limits the scaling of AQ monitors

• Sensor technology is advancing rapidly (e.g., optical sensors for particulate 

matter) but there is need for additional research and testing for many existing 

and emerging air quality pollutants;

• Gaps in local (community) scalable air quality monitoring to support a variety 

of use cases, including 

o Increasing public awareness of AQ 

o Informing environment and public policy; real time testing of policy 

impacts

o Environmental justice work

o Supplementing regulatory grade sensing with commercial sensors

o Public health research
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o Construction site emissions monitoring

o Rapid or emergency AQ monitoring

Implementation Considerations:

The EPA should consider amendments to the Code of Federal Regulations 40 Part 50, 

to encourage implementation of IoT AQ sensing devices to augment regulatory FRM 

and FEM Methods for air quality monitoring.

• Need top down demonstration by EPA and it’s State, Local and Tribal partners, 

as well as concrete policy methods, by which to improve implementation of IoT 

devices and facilitate the incorporation of this incorporate this data into 

government data. 

• Facilitate research and testing in low-cost sensing technologies for many 

existing and emerging air quality pollutants

• Facilitate the use of space at federal infrastructure (e.g., post office buildings) 

and federal assets (e.g., post office delivery vehicles) for locating academic and 

private sector air quality monitors. 

• Facilitate and support research and a program in correlating regulatory grade 

data with AQ data 

• Push state/city to facilitate the expansion of wireless connectivity to support 

remote monitoring and sensing in areas not serviced by traditional connectivity 

(e.g., TV white space, satellite). 

Enabling Recommendation ER5.6.3: The government should implement a 

nationwide IoT-based Water Monitoring Infrastructure) to expand the 

nationwide water monitoring system, including water treatment facilities.

Supported by Finding x.x

Develop a comprehensive, nationwide water monitoring infrastructure that leverages 

IoT technology for real-time, accurate, and cost-effective water quality and quantity 

data collection. This infrastructure should support data-driven decision-making, 

address the challenges of water scarcity, contamination, and climate change, and 

integrate with existing NOAA water models for enhanced forecasting and 

management capabilities. 

Current water monitoring systems are often fragmented, inefficient, and insufficient 

to address the growing challenges of water management.

IoT technology enables real-time, remote, and continuous data collection, allowing for 

proactive responses to water-related issues.
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Integration with NOAA water models can enhance forecasting and management 

capabilities, leading to more effective water resource planning and allocation. 

Efficient water management is crucial for consumption, agriculture, and industry, 

ultimately contributing to environmental and economic sustainability.

Implementation Considerations:

Develop a standardized, nationwide framework for water monitoring, including 

protocols for data collection, transmission, storage, and analysis.

Encourage the adoption of open data standards and APIs to ensure interoperability 

among different IoT devices, platforms, and NOAA water models.

Allocate resources for research and development of advanced IoT sensors, data 

analytics tools, and communication networks that can seamlessly integrate with 

NOAA's existing water modeling systems.

Support pilot projects that demonstrate the potential of IoT in water monitoring and 

management, as well as the successful integration with NOAA water models, and 

scale up successful models through federal and state programs, grants, and 

incentives.

Enabling Recommendation ER5.6.4: The government should utilize IoT 

Technologies to facilitate carbon transparency across economic sectors. 

Supported by Finding x.x

Promote the adoption of IoT-based solutions across multiple economic sectors to 

accurately estimate and manage indirect carbon emissions associated with goods 

and services. By leveraging IoT technologies, greenhouse gas emissions associated 

with upstream and downstream supply chains (scope 3 emissions) can be measured, 

collected, and compiled for the manufacturing, transportation, agriculture 

production, and end-of-life practices for economic activity. Great transparency of 

scope 3 emission with enable the implementation of effective mitigation strategies 

and contribute to national and global efforts to reduce carbon emissions. 

These actions are particularly important because:

• Greenhouse gas reporting protocols are recently experiencing increased 

adoption and many of these reporting protocols include greenhouse gas 

emissions beyond those associated emitted at the company’s site (scope 1) and 

emissions associated with the generation electricity that the company 

consumes (scope 2). These indirect, “scope 3” emissions can be challenging to 
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monitor since they are distributed across supply chains of products and 

services a company uses (e.g., the transportation of the company’s product)

• Accurate monitoring and estimation of scope 3 carbon emissions across 

economic sectors can help identify indirect but significant emission hotspots 

and develop targeted mitigation strategies.

• IoT technologies enable real-time, remote, and continuous data collection, 

allowing for systematic management of carbon emissions at reduced cost and 

effort.

• Combining IoT-based monitoring with other estimation methods can improve 

the accuracy and reliability of scope 3 emissions data. 

Implementation Considerations:

• Develop a standardized framework for the integration of IoT technologies in 

scope 3 carbon emissions monitoring, including protocols for data collection, 

transmission, storage, and analysis. 

• Encourage research and development of advanced IoT sensors and data 

analytics tools specifically designed for estimating greenhouse gas emissions 

across supply chains. 

• Support pilot projects that demonstrate the potential of IoT in estimating and 

mitigating carbon emissions across sectors and scale up successful models 

through federal and state programs, grants, and incentives.

• Provide training and technical assistance to stakeholders in the 

implementation and maintenance of IoT-based carbon emissions monitoring 

systems.

• Facilitate collaboration and data sharing among stakeholders, researchers, and 

policymakers to promote informed decision-making and the development of 

best practices for emissions reduction.

• Include the use of IoT technologies in grants for carbon emissions monitoring

Enabling Recommendation ER5.6.5: The government should facilitate and 

promote the use and integration of IoT technologies to complement and 

support wide area environmental situational awareness capabilities to 

monitor and inform on a variety of environmental conditions and hazards 

in environmentally sensitive areas.

Supported by Finding x.x
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The use of proprietary technologies and systems are common in systems used to 

monitor various environmental conditions for first responder, scientific research, and 

safety applications. 

The federal government should facilitate and promote the use and integration of IoT 

technologies to complement and support wide area environmental situational 

awareness capabilities to monitor and inform on a variety of environmental conditions 

and hazards in environmentally sensitive areas. Examples of opportunities where IoT 

technologies should be incorporated include forest monitoring, wildfire monitoring, 

earthquake detection, flood, air quality, etc.

Many existing environmental monitoring platforms today use proprietary 

technologies. One example are the stream gauges used by various federal and state 

agencies, local governments and private water rights owners to monitor water flow 

conditions to determine river health and warn on flooding situations. Data collected 

from proprietary systems are not easily shared nor integrated with data from other 

sources, thus limiting timely analysis and responsive actions.

Environmental situational awareness monitoring is critical to ecological health, public 

safety and disaster recovery. For example, a dense network of low cost IoT-enabled

gas sensors can be used in conjunction with a network of cameras to detect and 

pinpoint wildfires. Early detection of wildfires in remote forests allows firefighters to 

direct resources to the initial location, increasing the odds of combating the fire before 

it becomes widespread. A network of IoT-enabled air quality, earthquake, and other 

sensors integrated together allow state and regional agencies to build real time 

situational awareness capabilities to support and plan activities that preserve 

ecologically sensitive areas, mitigate, respond and recover from natural and manmade hazards.

Implementation considerations:

• Specification of IoT technologies into grants and federal procurements for 

environmental monitoring and situational awareness

• Collaboration with federal, state and regional agencies to define missions and 

requirements

• Monitoring of wide areas, especially in areas not monitored before or remote 

areas, may require new connectivity methods, such as satellite and other 

approaches
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Smart Transportation

Key Recommendation KR5.7: The government should implement specific 

actions to promote IoT adoption in Smart Transit and Transportation. 

Supported by Finding x.x

Smart transit and transportation technologies provide an organized, integrated 

approach to minimizing congestion and improving safety on streets through 

connected technology. These technologies smooth traffic flows and prioritize traffic 

in response to demand in real time. They enhance pedestrian, bicycle and vehicle 

safety and reduce accidents that cause injuries and fatalities. 

Enabling Recommendation ER5.7.1: The government should promote the 

development and adoption of policies, procedures and funding methods 

that can accelerate the adoption of smart, connected, and electrified 

transportation technologies. 

Supported by Finding x.x

Many of these transportation technologies incorporate the use of IoT. Federal 

funding can also serve to increase private sector investment.

Greater adoption of smart, connected, and electrified transportation technologies 

could help in the following examples:

• Incorporation of technologies enabled by IoT: Opportunities for IoT 

technologies in smart, connected transportation include sensors, cameras, and 

edge computing devices that can improve safety in things such as vulnerable 

road users (i.e., pedestrians at crosswalks), traffic intersections, school and work 

zones. Opportunities for IoT technologies in electrified transportation include 

in car systems or mobile apps that can locate charging stations, as well sensors 

that manage charging stations to gather data about usage and performance, 

to anticipate maintenance needs, and troubleshoot problems. 

• Improving overall traffic safety: Vehicles that have technologies such as Cellular 

Vehicle to Everything (C-V2X) can communicate basic safety messages and 

information to corresponding infrastructure and other road users thereby 

reducing traffic and pedestrian fatalities. 
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• Reduction in greenhouse gas emissions: The transportation sector generates 

the largest share of greenhouse gas emissions a big contributor to climate 

change. Electrification of transportation away from traditional fossil fuels are a 

viable option for transportation. Also smart, connected transportation can 

improve traffic flow and reduce congestion which is also better for the 

environment. 

Implementation considerations:

With the Bipartisan Infrastructure Law (BIL) and the Inflation Reduction Act (IRA) the 

Federal Government is already taking steps to electrify the transportation sector. 

Funds are being directed to the states to deploy electric vehicle charging stations via 

the NEVI Formula Program (https://afdc.energy.gov/laws/12744). Under the IRA tax 

credits are available for EVs that are primarily assembled in North America. It is 

important that this legislation stays in effect throughout its designated time period. 

While the BIL and the IRA are significant pieces of legislation, additional legislation is 

probably needed to focus on rural communities. 

Additionally, the Federal Government could set aside easily and readily tappable 

funding pools year-round for innovation and next-generation technologies. Grants 

could be set aside for categories that the government deems high importance. The 

government could also leverage innovative procurement technologies like outcomesbased contracting in surface transportation. (https://www.nema.org/docs/defaultsource/nema-documents-libraries/whitepaper-on-outcomes-basedcontracting.pdf?sfvrsn=f3ad2716_2) 

Earlier this year ITS America published the National V2X Deployment Plan which 

includes a call to action for the federal government, as well as state and local 

transportation agencies, automotive OEMs, and other stakeholders to install V2X 

systems for public safety – beginning with signalized intersections, other road users 

and selected production vehicles (https://itsa.org/advocacy-material/its-americanational-v2x-deployment-plan) 

Facilitating an IoT-enabled Economy 

Objective 6: The U.S. can facilitate economic and societal benefits by taking 

specific actions to advance the integration of IoT with supply chain operations, 

public-private partnerships, and artificial intelligence.
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Key Recommendation KR6.1: The government should monitor and evaluate 

progress of IoT adoption for supply chain logistics. 

Supported by Finding x.x

The government should provide an intentional process to monitor and evaluate 

progress to provide assurance that IoT adoption efforts in supply chain logistics are on 

track, effectively addressing identified challenges and opportunities, and delivering 

desired outcomes. The need to monitor and evaluate progress in IoT adoption for 

supply chain management stems from the need to ensure the effectiveness of 

implemented strategies, measure their impact, and identify areas for improvement. 

By regularly monitoring and evaluating the progress of IoT implementation, the 

government can identify areas of improvement, assess the impact of its policies and 

initiatives, and make informed decisions to optimize its strategies and investments in 

the future. Monitoring and evaluating progress involves establishing a set of 

measurable indicators and targets that reflect the key objectives and desired 

outcomes of IoT adoption in supply chain management. These indicators may include 

the level of IoT technology adoption, efficiency gains, cost reductions, improvements 

in transparency and traceability, and advancements in cybersecurity, among others. 

Regular assessments should be conducted to track the progress of IoT adoption 

against the established targets, identify any gaps or challenges, and evaluate the 

effectiveness of the implemented policies and initiatives. Based on the findings of 

these assessments, the government should adapt its strategies and actions to address 

the identified issues, optimize resource allocation, and maximize the impact of its 

efforts. By monitoring and evaluating progress, the government can ensure that its 

approach to driving IoT adoption in supply chain management remains agile, 

responsive, and results-oriented, ultimately contributing to the long-term success 

and competitiveness of the industry. 

Implementation Considerations: 

• Establish clear goals and objectives: Define specific, measurable, and timebound goals and objectives for IoT adoption in supply chain management to 

enable effective monitoring and evaluation.

• Develop relevant performance indicators: Identify key performance indicators 

(KPIs) that reflect the desired outcomes of IoT adoption and can be used to 

measure progress and impact. 

• Implement data collection and reporting mechanisms: Set up systems and 

processes for collecting, storing, and analyzing data related to IoT adoption and 

supply chain performance. 
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• Conduct periodic assessments: Schedule regular evaluations of progress and 

impact, using the collected data and KPIs to assess the effectiveness of IoT 

initiatives in supply chain management.

• Foster a culture of continuous improvement: Encourage feedback and learning 

from monitoring and evaluation results, using the insights to improve and 

refine policies and initiatives.

• Collaborate with stakeholders: Engage with industry, academia, and other 

relevant stakeholders to gather their insights and perspectives, ensuring a 

comprehensive understanding of progress and challenges.

• Assign responsibility: Designate a lead federal agency or interagency group 

responsible for overseeing the monitoring and evaluation process for IoT 

adoption in supply chain management.

• Develop a monitoring and evaluation plan: Create a detailed plan outlining the 

goals, objectives, KPIs, data collection methods, and evaluation schedule.

• Allocate resources: Ensure adequate financial, human, and technical resources 

are allocated to support monitoring and evaluation activities. 

Public and Private Partnership

Key Recommendation KR6.2: The government should help establish and 

foster public-private partnerships (PPPs) focused on IoT adoption to 

facilitate collaboration and knowledge sharing between government 

agencies, businesses, technology providers, and academia.

Supported by Finding x.x

The federal government should lead the formation of collaborative public-private 

partnerships (PPPs) to accelerate the adoption of Internet of Things (IoT) technologies 

within supply chain logistics operations. These partnerships bring together a diverse 

array of stakeholders, including government agencies such as the Department of 

Commerce, logistics providers, IoT technology companies, and academic institutions 

such as MIT's Center for Transportation & Logistics. The resultant platform would 

foster collaboration and knowledge exchange, stimulating the development, 

deployment, and wider adoption of IoT technologies in supply chain management.

PPPs can address common barriers to IoT adoption, including infrastructure gaps, 

limited technical knowledge, and financial constraints. By aligning efforts and pooling 

resources, these partnerships can drive the innovation of IoT solutions, initiate pilot

projects, and roll out proof-of-concept initiatives that demonstrate the value and 

benefits of IoT in supply chain operations. Additionally, they can contribute to 

workforce development by creating and supporting training programs, potentially in 

collaboration with technical colleges and universities.
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They also play a role in establishing industry standards and regulatory frameworks 

conducive to IoT adoption across the supply chain industry. This would involve close 

collaboration with regulatory bodies like the Federal Communications Commission 

(FCC) and standard-setting institutions like the National Institute of Standards and 

Technology (NIST). By fostering such partnerships, the government can nurture a 

thriving ecosystem that drives innovation and competitiveness in the supply chain 

sector, maximizing the potential of IoT technologies.

Implementation Considerations:

• Identifying key stakeholders: The federal government should identify relevant 

private sector stakeholders, including businesses, industry associations, 

research institutions, and technology providers, who can contribute to the 

development and implementation of IoT solutions in supply chain 

management.

• Establishing a collaborative framework: A formal framework should be 

established to facilitate collaboration between the public and private sectors. 

This may include creating joint working groups, industry forums, or innovation 

hubs, where stakeholders can share ideas, knowledge, and resources.

• Defining clear goals and objectives: Public-private partnerships should have 

well-defined goals and objectives that align with the overall strategy for 

promoting IoT adoption in supply chain management. This will help ensure 

that all stakeholders are working towards a common vision and can measure 

their progress.

• Developing joint projects and initiatives: The federal government and private 

sector stakeholders should collaborate on joint projects and initiatives that 

address specific challenges or opportunities in supply chain management. 

These could include pilot projects, research and development programs, or the 

development of new IoT standards and protocols.

• Ensuring effective communication and coordination: Open and transparent 

communication between the public and private sectors is critical for successful 

collaboration. Regular meetings, progress reports, and information sharing 

mechanisms should be established to facilitate coordination and maintain 

momentum.

• Monitoring and evaluation: The federal government should establish a system 

for monitoring and evaluating the effectiveness of public-private partnerships 

in promoting IoT adoption in supply chain management. This may involve 

tracking key performance indicators, such as the number of joint projects 

implemented, the amount of private investment leveraged, and the impact on 

supply chain efficiency and resilience.
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Enabling Recommendation ER6.2.1 The government should foster 

orchestrated Public-Private Partnerships (PPPs) promoting network 

effects among connected enterprises and across supply chains. 

Supported by Finding x.x

To speed up the creation of connected supply chains the government should promote 

PPPs that promote network effects to speed the adoption of end-to-end digital 

threads using consistent digitalization methods capturing receivables, processes, and 

certified deliverables.

The federal government can accelerate the creation of traceable supply chains by 

encouraging the orchestration of connected Private-Public Partnerships (PPPs) 

promoting network effects among stakeholders across complex supply chains who 

maintain Trust through collaboration by digitalizing portions of supply chains 

piecemeal using consistent methods of “receivables-process-deliverables”. 

Digitalization across supply chains of PPPs collaborating in parallel can help 

accelerate the adoption of digital threads and become more efficient which will help 

businesses to grow digital revenue streams on top of IoT products and services that 

drive economic growth. 

Examples:

• Orchestrated PPPs can accelerate the adoption of end-to-end digital thread 

and traceability in complex supply chains, by digitalizing portions of solutions 

supply chains or supply chains piecemeal in parallel using consistent methods. 

• Collaboration and accountability among enterprises in IoT supply chains can 

create resilient and secure supply chains that can help businesses drive 

economic growth.

• Traceability can help businesses reduce risk, increase resilience, and protect 

against supply chain risks of vulnerabilities, intrusions, and adversaries, which 

can lead to business and economic growth. 

• Trustworthiness across IoT supply chain with secure infrastructure can drive 

shared monetization among stakeholders leveraging fintech to enable scalable 

economics.

Implementation Considerations

• Encourage the orchestration of connected Private-Public Partnerships (PPPs) 

across complex value chains, by providing incentives for businesses to adopt 

transparent workflow practices and engage in pilot projects to prove the value.
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• Promote consistent digitalization methods for "receivables-processdeliverables" across supply chains by digitalizing portions of supply chains 

piecemeal to facilitate parallel collaboration among stakeholders. Network 

effects can accelerate adoption and growth.

• Fund the development of digital infrastructure, training programs, and other 

resources necessary for successful partnership implementation. All 

requirements are shared responsibility among all PPP stakeholders.

• Create a taxonomy of entities in market-specific supply chains that can be 

orchestrated to maintain trust through orchestration, collaboration, guidelines, 

and standards among stakeholders in connected supply chains. 

Enabling Recommendation ER6.2.2: The government should subsidize 

initiatives for digital infrastructure supporting the digital transformation of 

enterprise business processes including design, production, procurement, 

distribution. 

Supported by Finding x.x

The digitalization of all business functions (design, production, marketing, 

procurement, distribution, etc.) enables more efficient IoT product management, 

greater visibility, and transparency over supply chains to track products, monitor 

quality, and fix issues or defects. By using cryptographic methods, digitalization can 

have a major impact in improving the security, reliability, integrity, and trust of data 

for the digital economy. By providing incentives for businesses to adopt digital tools, 

the federal government can help promote ecosystems that create opportunities for 

businesses and workers in any value chains which will drive economic growth.

Furthermore, digitalization enables digital transformation whereby IoT device 

suppliers become connected to their customers which enables sustainability and 

circular economy. 

Implementation Considerations: 

• Develop and communicate clear guidelines and criteria for eligibility for the 

subsidies. 

• Incentivize Orchestrated PPPs to work on Proof of Concept (PoC) projects to 

assess the economic value before investing in solutions to deploy at scale. 

• Create a streamlined application process for businesses to apply for subsidies. 

• Ensure that the funds are accessible to businesses of all sizes and types in the 

IoT value chain. 

• Monitor the effectiveness of the funds allocated to PPPs to ensure that they are 

achieving the intended outcomes. 
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• Provide incentives for businesses to invest in digitalization and adopt digital 

technologies and tools. 

• Encourage knowledge sharing among businesses to promote best practices. 

Enabling Recommendation ER6.2.3: The government should promote the 

enablement and use of trusted digital threads, trusted digital 

marketplaces and platform-based business ecosystems.

Supported by Finding x.x

As digital threads and digital platforms emerge, the government should promote the 

enablement and use of these tools to drive economic growth with trusted data 

exchange and licensing while protecting the proprietary IP of enterprises in the value 

chain.

In the most general case, digital threads are the flow of data that connects business 

processes, products, and assets across supply chains, networks, or applications. In a 

narrower sense within the supply chain, each component (chip, software, module, 

device) has associated information regarding provenance, integrity, version and more. 

As components are associated with modules and the modules with assembled 

devices running software, this flow of data through the supply chain has the potential 

to inform security, product integrity and availability. Ideally, all of this information—

this “digital thread”—is and remains available throughout stages of the supply chain, 

from original materials through installed systems.

A trusted digital thread benefits from cryptographic protection in each stage and 

throughout the flow. This information is valuable and can be exchanged in digital 

marketplaces. The government should incentivize the enablement and use of trusted 

digital marketplaces where producers and consumers query and share information 

about assets and related data, enabling better visibility, traceability, and monetization 

while protecting proprietary IP and PII. 

Trusted digital marketplaces can be promoted through pilot programs, best practices 

and guidelines. Platforms that facilitate adoption of digital marketplaces can enable 

producers and consumers to reduce costs and improve efficiency. Efficiencies come 

from streamlining processes and eliminating redundancies, especially in complex 

supply chains where information flows are often fragmented or disconnected. 

Furthermore, trusted digital marketplaces driven by digital threads enable 

participating stakeholders to evolve new business models and revenue streams. 

When these are combined with business platforms that maximize network effects, it 

will fuel the growth of ecosystems and future digital economies.
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Implementation Considerations: 

• Identify standards, taxonomies, and best practices to define supply chain 

trusted digital threads and marketplaces. 

• Identify suitable marketplaces to incentivize and support (e.g., EV charging and 

monetization). Develop guidelines and incentives for access and use of data.

• Promote the benefits of data marketplaces to potential participants and 

provide tax credits and subsidies to encourage participation. 

• Ensure data security and confidentiality measures are in place. Monitor and 

evaluate the effectiveness of the data marketplaces. Use analytics to improve 

visibility, traceability, efficiency, and cost.

Key Recommendation KR6.3: The government should actively promote and 

support the adoption of AI applications to improve decision-making, 

optimize resource utilization, and enhance productivity. 

Supported by Finding x.x

AI applications have the potential to revolutionize the way workers in many sectors 

analyze and use IoT data. By leveraging advanced algorithms and machine learning 

techniques, AI can enable personnel to identify patterns, optimize resource allocation, 

and make better informed decisions. This will result in benefits for various 

stakeholders, including business owners, policymakers, and consumers. 

Federal stakeholders could establish a public-private-academia partnership that 

would define specific applications that would benefit from AI. Agencies could support 

the partnership through financial incentives and subsidies, and through formal 

promotion of education and training opportunities (perhaps in concert with other 

workforce efforts described.) 

The government could also create educational programs and resources to help 

professionals understand the benefits of AI technology and how to effectively 

implement and use these applications. This can be achieved through collaborations 

with extension centers, universities, and industry experts. Agencies could also offer 

workshops, webinars, and online courses to ensure widespread access to knowledge 

and training opportunities. 

Enabling Recommendation ER6.3.1: The government should promote 

trusted AI-IoT platforms across circular supply chains and ecosystems to 

improve transparency and sustainability and drive economic growth.

Supported by Finding x.x
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The government should promote trusted AI-IoT (“AIoT”) platforms within circular 

value chain ecosystems. Circular supply chain ecosystems are those sustainable cycles 

where resources remain as much as possible in the loop of collection and processing, 

production and purchasing, consumption and use. Key is that resources can be cycled 

back again in these stages by use of sustainable processes of, e.g., remanufacture or 

recycling. Use of AIoT can enhance transparency, sustainability, and economic growth

by fostering innovation and efficiency which will benefit businesses, the environment 

and digital economy.

Promoting trusted AIoT platforms within circular supply chain ecosystems is 

imperative for ensuring transparency, sustainability, and economic growth. This 

initiative not only fosters innovation but also enhances efficiency, benefiting 

businesses, the environment, and the future digital economy. By strategically 

integrating AIoT into circular supply chains, the government can create a foundation 

for responsible and sustainable technological advancement, positioning the nation as 

a leader for the global digital economies.

Examples include:

• Innovation Hubs: Promoting AIoT platforms will drive innovation, enabling the 

development of cutting-edge technologies and solutions.

• Efficiency Boost: AIoT can optimize resource utilization, reducing waste and 

energy consumption within circular supply chains.

• Environmental Benefits: Sustainable practices fostered by this initiative can 

help combat climate change and promote eco-friendliness.

• Economic Growth: The growth of AIoT-driven industries will create jobs and 

stimulate economic development.

• Competitive Advantage: By embracing AIoT, the nation can establish itself as a 

pioneer in the digital economy, attracting global investments.

Implementation Considerations:

• Public-Private Partnerships: Encourage collaboration between government, 

businesses, and research institutions to drive innovation.

• Sustainability Standards: Establish clear sustainability guidelines for AIoT 

projects within circular supply chains.

• Data Governance: Develop robust data governance policies to protect privacy 

and promote transparency.

• Education and Training: Invest in workforce development and educational 

programs to prepare individuals for AIoT-related jobs.
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Conclusion

• A concluding statement from the report that summarizes the work and the 

findings and that encourages continued progress from the Board.

• A cordial invitation for follow-up questions, if needed and as permitted by the 

FACA process.

• Thank you to the IoT Advisory Board members for their contributions and 

support.
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References 

Specific documents cited in the report (end notes) (standards, guidelines, policies) 

(with hyperlinks). 

The following international data transfer agreements may have an impact on IoT: 

Global Asia-Pacific Economic Cooperation (APEC) Cross-Border Privacy Rules (CBPR)

Canada, Japan, the Republic of Korea, the Philippines, Singapore, Chinese Taipei, and 

the United States of America are current economies participating in the APEC CBPR 

System

https://www.commerce.gov/news/press-releases/2022/04/statement-commercesecretary-raimondo-establishment-global-cross-border [commerce.gov] 

EU-U.S. Data Privacy Framework (EU-U.S. DPF) - Privacy Shield Replacement

https://www.commerce.gov/news/press-releases/2023/07/statement-us-secretarycommerce-gina-raimondo-european-union-us-data [commerce.gov]

U.S. & UK Data Bridge (Added to the Privacy Shield Replacement) 

https://www.commerce.gov/news/press-releases/2023/06/us-uk-joint-statement-usuk-data-bridge [commerce.gov]

Acknowledgements 

This section will acknowledge the work of groups or individuals (outside of the Board 

itself, which is listed elsewhere) who have contributed to the project. Such 

contributions include support for meetings, useful discussions, or extensive copyediting of the publication.

Include speakers with links to meeting materials
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Appendices

• Other selected industry references (standards, guidelines, corporate reports) 

considered during discussions and for recommendations.

• Other Federal regulations and statutes affecting IoT

• Summaries of other federal reports supporting IoT improvement / actions

• Glossary of Selected Terms

• Abbreviations / Acronyms

• Other ideas?

Appendix A: IoT Stakeholders

The Internet of Things (IoT) provides the potential significant economic and societal 

benefits to individual personas, communities, businesses, and academic and 

government organizations across the United States. Some of these benefits provide 

incremental value, while others are more significant and transformational. The 

benefits offered by IoT are not uniform but vary across groups of people, organizations, 

and application markets. The benefits range from positive outcomes from the use of 

IoT to creation of new jobs related to IoT and those indirectly related to IoT. This section 

provides a brief description of which stakeholders and personas are impacted, and in 

what ways.

Manufacturers

IoT in manufacturing can best be categorized via the following types: companies that 

design and manufacture chips and modules (i.e., Intel, Qualcomm, Samsung), 

companies that assemble modules and produce branded products (i.e. Cisco), 

contract manufacturers that receive a chip design and deliver a packaged chip (i.e. 

GlobalFoundries), and manufacturers who receive a design and Bill of Materials, 

assemble them as part of their manufacturing operations, and deliver a finished 

product (i.e. Rockwell). There are two types of manufacturers involved with the 

production of IoT. Component manufacturers produce the basic IoT products that are 

used in the development of IoT-enabled “smart” products. For example, 

semiconductor and sensor manufacturers produce the core components used in IoT 

devices. Module manufacturers then purchase and assemble these semiconductors, 

radios, and sensors together to build modules that brand developers (see below) and 

device manufacturers purchase. 

Manufacturers benefit from IoT in a variety of ways. The demand for IoT products 

creates significant direct and related revenue, jobs and business expansion 

opportunities in a variety of markets. IoT products generate immediate revenue for 

existing products, as well as pull through demand for other higher margin products, 
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such as faster processors, storage devices, and sensors. For example, the continuing 

evolution of IoT demand has created the need for higher price and margin AI capable 

microprocessors. In addition, the buildout of IoT systems creates demand for edge 

servers and storage. 

Manufacturers face a variety of barriers. The fragmented nature of the IoT ecosystem 

adds confusion and complexity in the marketplace and hinders adoption. Slower than 

expected market adoption of IoT hinders manufacturer investment and continuing 

product evolution. Overseas competition creates margin pressure on domestic 

suppliers and limits business expansion. Supply chain disruptions limit the ability to 

produce enough products and components to meet customer orders. Manufacturers 

of hardware products have an opportunity to alleviate such barriers by making their 

products smart-connected IoT products and offer new services including remote 

support and new Hardware as a Service capabilities.

Developers

In the IoT ecosystem, there are various types of developers. “Brand developers” are 

businesses whose core product is not IoT but incorporate and integrate IoT 

technologies into their existing products. For example, a machine tool manufacturer 

incorporates IoT into their product line, to create “smart milling machines”. The brand 

developer buys or licenses the IoT technology from a 3rd party, or contracts with a 

product development firm to develop it for them. 

“IoT technology developers” offer hardware, software, and cloud application 

development services. They contract with brand development companies to create 

IoT or IoT-enabled products. Technology developers may also work with 

implementers (see below) to create custom IoT applications to support business, 

government and other organizations using IoT. Examples of IoT technology 

developers include product development firms, software development firms, and 

original design manufacturers (ODM).

IoT offers brand developers a variety of benefits. The addition of IoT to an existing 

product line creates new value and enables the brand to charge higher prices and is 

often accomplished with partnerships. The IoT-enabled product line may generate 

new revenue streams from recurring subscription based models arising from better 

visibility to the end application including online support, quicker turnaround time of 

RMAs and bug fixes, and upgrades based on customer changing needs

In addition, the new product line may be more attractive to buyers and allows the 

brand to expand existing markets and enter new ones. Overall, IoT helps brand 

developers increase revenues, create recurring revenue opportunities and enhance 

profitability.
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Brand developers face a number of barriers. Digital products require a business 

process change including infrastructure, operational capabilities, functions, skills, and 

resources that are different compared to non-digital products. The addition of IoT and 

digital technologies to traditional businesses and business models brings new 

complexity and requirements that they may not have the expertise, skills, resources 

and infrastructure to support. Adding digital capabilities to traditional product lines 

creates new issues and risks, such as cybersecurity, privacy and interoperability and 

liability that the developer is unaware of. 

New business and operating models enabled by IoT require significant investments 

that brand developers may be unwilling to commit to or may not be able to sustain 

for long. Despite the brand developer’s reputation, customers may not be willing to 

adopt the new IoT-enabled products because of the higher risks associated with 

cybersecurity and privacy vulnerabilities. Some brand developers pursue a path of 

digitalization to upgrade the existing infrastructure before embarking to digital 

transformation which involves A broader business prices change.

Implementers

Implementers are businesses who resell, install and set up, and maintain and service 

IoT and IoT-enabled equipment to corporate, government, consumers and other 

buyers. Some businesses, such as retailers, only resell, but not install or service these 

IoT products, while others offer a full range of services. Typically, the more complex 

the IoT product is, the more services the implementers offer. Implementers may 

contract with IoT technology developers to build and implement custom solutions. 

For example, a HVAC contractor sells a smart HVAC system to a building owner. The 

contractor will install it, connect it to the network and the building energy 

management system, configure and test it for proper operation. They sell the building 

owner a maintenance contract, which requires them to come back on a quarterly 

basis to maintain the system and optimize its performance. On the other hand, a 

retailer may only sell a IoT solution but require the buyer to install and set up the 

solution or find a 3rd party to do so. 

For implementer businesses, IoT provides a wide range of benefits. For example, IoT 

enables to sell add-ons to existing products, or new products, services, leading to a 

new source of revenue. IoT enables implementers to create new businesses and 

services on top of existing products and services. This leads to new revenues from

existing customers, or new revenues from new customers. Many of the business 

models enabled by IoT enable implementers to shift away from “one-time” 

transactional sales to create long lasting recurring revenue streams from subscription 

services.
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Implementers face a number of barriers that hinder their ability to develop, operate 

and sustain their businesses. Their existing workforce may not be well suited to 

support and service these new technologies. There is a lack of a suitable and sufficient 

workforce with the digital skills and capabilities to install, integrate, configure and 

optimize these technologies. While IoT enables to create new business models, 

transitioning to those business models are operationally challenging because they 

may require business process changes and digital transformation, or a shift away from 

“one-time” large revenues, to recurring small revenues. This requires changing 

operational and business models. While IoT may offer new long lasting value, 

customer adoption of these technologies may take longer. These long sales cycles 

may drive implementers to abandon these products and services in favor of traditional 

“tried and true” offerings that drive sales for the business now.

Administrators

Administrators are the owners and buyers of IoT and IoT equipment for business, 

government and other organizations. They are responsible for the overall 

management of these technologies and systems, including procurement, integration, 

operation, maintenance and optimization within the organization. IoT technologies 

bring together traditional separate functions together, including information 

technology, operations, and the business units (marketing, technical support, finance 

and others). Administrators may perform some or all of these functions, or they may 

contract with 3rd parties, including implementers and developers, to conduct these 

activities. Administrators may reside in each of these organizations, or they may be 

centralized in a single organization.

Administrators are concerned with the benefits of IoT from an organizational 

perspective. The benefits of IoT depend on the application and usage, but include 

increased revenues, cost savings and profitability. IoT can create or enhance services 

and products, and lead to new revenue streams. The usage of IoT may lead to cost 

prevention, increased operational efficiencies, and staff and resource effectiveness. 

Other benefits include increased customer satisfaction, retention and loyalty.

Administrators face a number of barriers to IoT adoption in their organizations. These 

include cybersecurity and privacy concerns, and complexities in integrating IoT into 

existing information technology (IT) and operational technology (OT) or industrial 

processes and systems. The joining together of IT into OT and industrial operations 

creates resistance as it requires these separate functions and teams to break out of 

silos to work together. Job roles and responsibilities will change and the workforce 

may not have the modern digital skills, in integration, data science and programming, 

to fully utilize these systems. 
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Operators

Operators are users that use IoT products and IoT-enabled equipment to carry out 

their day to day jobs in a business, government or other organization. For example, 

operators in a factory use sensors to monitor and control the manufacturing process 

to increase finished product quality and reduce scrap. Operators in a power 

generation facility use sensors and analytics to monitor critical turbine performance 

to minimize unplanned downtime. Technical support staff remotely monitor sensor 

data to diagnose equipment deployed in the field. Resellers monitor how customers 

are using their equipment and make recommendations to optimize performance and 

outcomes. Facilities operators monitor a building's sensors and systems to optimize 

comfort, energy usage and operations.

While the benefits to operators vary by operator organization, there are some 

common benefits. These include higher productivity and performance, reduced 

quality defects and customer complaints, increased proactiveness and 

responsiveness to customer needs, reduced operating downtimes and inefficiencies, 

and lower operating costs and staffing resources, which collectively reduce OPEX.

Operators face a variety of barriers hindering adoption and the full realization of 

benefits. Operators may require training and reskilling in digital and data skills to 

properly use IoT-enabled equipment. While IoT increases operations visibility and 

leads to more transparency and accountability, it may also be perceived as “worker 

tracking” and is resisted by employees and their unions. Operators may resist 

adoption because they fear that IoT leads to operational efficiencies, automation and 

less need for staff. Some operators feel that their “tried and true” experiences and 

intuition is more relevant and resist the use of the IoT technologies. Finally, the use of 

IoT may lead to changes in roles and responsibilities, which operators may not be 

comfortable with or suited for.

Consumers

Consumers purchase and use IoT and “smart” products for their personal or family 

use. For example, they use “smart watches” to monitor their health and physical 

activities, receive and communicate messages, and run a variety of apps. They use 

“tracker” devices to locate their wallets, handbags, keys, luggage and other things. 

They use “smart assistants” to turn on and off appliances and other devices, get 

information, listen to music, communicate and run “voice apps”. They use “smart 

thermostats” to keep the home at a comfortable temperature and save on energy 

bills. They also use connected cars for real-time navigation, vehicle health monitoring, 

Bluetooth mobile phone connectivity and personalized driving experiences. 
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IoT provides a variety of benefits to consumers, including saving money and time, 

increased convenience and peace of mind, improved awareness, health, safety and 

performance. The actual benefits vary by IoT devices and their intended uses. 

Consumers face a variety of barriers and concerns that hinder adoption, and their 

ability to fully realize the benefits of IoT. Consumers are concerned about privacy, how 

the information collected is being used, and whether that information is used 

intentionally or unintentionally in a manner adverse to them. Consumers with low 

levels of digital literacy, as well as those with limited access to broadband service, may 

not be able to fully realize the utility and benefits offered by IoT. Products that are 

poorly designed, hard to set up and operate, result in consumers limiting their use of 

IoT or result in poor results. High product costs and subscription fees may preclude 

consumers who are on fixed incomes, or those that are on the lower end of the socioeconomic scale from having these devices.
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Appendix B: Leveraging U.S.-EU CHIPS Acts and IoT for Cross-Border 

Supply Chain Traceability to Strengthen National and Economic Security.

[Note: Tom K has provided this significant work which provides background and 

rationale for numerous recommendations. We are providing it as an appendix for 

group discussion, recognizing that many portions would need to be revised and 

included in the overview and findings sections.]

Background: In January 2024, the U.S.-EU Trade Technology Council convened to 

discuss transatlantic cooperation147 on trade and technology, covering export 

controls, AI governance, secure 5G connectivity, and semiconductor strategies based 

on the U.S.-EU CHIPS Acts. Later discussions as part of the Transatlantic Economic 

Security Agenda covered digitizing supply chains148 and chip traceability149. 

Subsequently, the White House launched a $5 billion fund for the National 

Semiconductor Technology Center (NSTC)150, while funds from the European CHIPS 

Act will be channeled through Chips JU151. 

Opportunity: The geopolitical landscape and CHIPS funding offer a unique 

opportunity to pursue cross-border chip supply chain traceability. Increased demand 

for IoT devices, digital transformation, supply chain fragmentation, and ineffective 

trade restrictions and sanctions on chips, underscore the mandate for the U.S., EU, 

and allied nations to invest in chip supply traceability starting from design and 

manufacturing. A digital traceability infrastructure linked to customs controls can 

maximize CHIPS investments by creating a market preference for assured and trusted 

chip supply. Moreover, it can reduce chip leakage to adversaries, strengthen national 

security and fuel economic growth.

Urgency: Geopolitical realities create urgency for chip traceability within global supply 

chains and obscure distribution channels. Traceability is vital to prevent our chips from 

being used in enemy systems and detect counterfeit or Trojan-laden chips targeting 

our critical infrastructure. IoT technology coupled with on-chip ‘Root of Trust’ is crucial 

for enforcing export controls on our advanced chips or preventing unauthorized use 

and in-field attacks. With over 70 fabs built globally backed by government funds it is 

urgent to invest proactively in traceability before these fabs surge into production.

Strategy: A cost-effective digital infrastructure using IoT for supply chain traceability 

will be key for the U.S. strategy on export controls for critical emerging technologies152. 

147 CSIS.org - The Fifth Ministerial of the U.S.-EU Trade and Technology Council 148 Atlantic Counsil - Gina Raimondo and Margrethe Vestager on future of US-EU economic ties 149 CSIS.org - The Transatlantic Economic Security Agenda (Promote, Protect, and Partner) 

150 Commerce.gov - White House Announces $5 Billion from the CHIPS Act for R&D and Workforce 151 ec.europa.eu - Commission launches Chips Joint Undertaking under the European Chips Act 152 CSIS.org - Optimizing U.S. Export Controls for Critical Emerging Technologies with Partners 
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It can increase demand for chips, mitigate risks, and boost our economy. By linking 

this infrastructure to chip design and manufacturing, new industries and workforces 

will emerge. These will use digital tools for supply chain logistics, tracking, auditing, 

and authentication. Suppliers will monitor chip flow within supply chains, tailor chip 

features to market needs, and manage in-field chip usage. This will fuel growth of IoT 

services and enable new business models to establish market preference, ensure chip 

supply, regulate market access, monitor field usage, and manage remote updates. 

Chip Supply Traceability Requires a Multi-stakeholder Ecosystem.

Increasing IoT Supply Chain Security Risks. Supply chain security and trust pose 

major concerns due to fragmentation and vast attack surface from chip design to IoT 

edge applications. Attacks experienced during field use of IoT devices such as DDoS 

attacks153 are often traced back to supply chain vulnerabilities due to bugs or 

intrusions in chips and electronics. The risks to national and economic security are 

growing rapidly.

Trade restrictions on chips are ineffective. Export controls for chips are not effective. 

Despite bans, U.S., and allied nations’ chips154 end up in Russian155 and Chinese 

drones156 altering modern warfare and affecting sea routes causing increased oil 

prices and cost of goods. Our advanced Artificial Intelligence chips are still being sold 

in China despite bans157. Imports are a challenge with Chinese legacy chips on track 

to flood markets158. 

Urgency for cross-border chip traceability. A study by KSE Institute159 shed light on 

flows of chips to Russia and the urgency to improve effectiveness. Solutions proposed 

153 Cybersecurity News - Why DDoS Attacks Use IoT Devices as Weapons? 154 Reuters - Chip challenge keeping western semiconductors out of Russian Weapons 155 Bloomberg - Chips from Texas Instruments and other US makers flow into Russia despite bans 156 Politico - A $2M missile vs. a $2,000 drone: Pentagon worried over cost of Houthi attacks 157 Reuters - China's military and government acquire Nvidia chips despite US ban 158 The Select Committee on the CCP - Letter to Secretary Raimondo on Foundational Semiconductors 159 KSE Institute - Challenges in export control enforcement
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included public-private partnerships on for chip supply traceability; export policy 

harmonization; sanctions on third-country intermediaries; enhanced cross-border 

cooperation among the U.S.-EU and allies; and use of IoT technology for tracing chips 

and disabling them remotely, ensuring export control enforcement before chips are 

used by adversaries.

Digital infrastructure and the Internet of chips. Enforcing export controls on 

advanced chips or monitoring the use of adversaries’ chips in our systems will be 

challenging since they can be programmed remotely. Intel’s pay-as-you-go chip 

licensing and Samsung’s chip rental service based on a Root of Trust signify the start 

of the “Internet of Chips” era. A trusted digital traceability infrastructure with customs 

controls that incentivize chip suppliers to securely trace, monitor and update chips 

can be more effective. It will unlock opportunities for trusted IoT services, digital 

marketplaces, and business ecosystems that can boost national security and fuel 

economic growth.

Supply Chain Provenance Starts from fabs. A global digital infrastructure for

traceability of chip supply starts from design and manufacturing. It requires 

coordination among chip suppliers, manufacturers, and consumers to establish 

provenance and chain of custody for assets/data across the IoT supply chain. This can 

be done through a digital flow of data connecting business processes, products, and 

assets (digital thread). 

Digital infrastructure and chip fingerprinting. A Root of Trust (RoT) inserted into 

chips during design and manufacturing, is key to ensure and trusted chip supply. One 

RoT placed on dies or chips tied to Physical IDs can help tracing physical chip assets. 

Another RoT inside the chip circuit creating a digital chip fingerprint upon power-up 

can help traceability of design assets. Data including bill of materials must be linked 

to these IDs.
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Trusted asset and data Tracking. When chips are sent to the supply chain, Physical 

IDs coupled with IoT technology like QR code RFID, can be used to track IoT device 

parts including hardware (HBOM), software (SBOM), and digital (DBOM) such as serial 

numbers, product SKUs, etc. This information can be furnished as metadata into a 

trusted digital thread enabling a digital marketplace of producers and consumers. 

Trusted digital twins accelerate adoption. Some CHIPS’ R&D funds will be invested 

in the Digital Twin Manufacturing USA Institute160. Digital twins are virtual models of 

physical assets, which enable to shorten the manufacturing process by using AI to 

improve efficiency161. IoT platforms with sensors deployed in manufacturing produce 

data used for AI and analytics across supply chains162. Trusted digital threads can be 

used by downstream create other digital twins and enable digital marketplaces. This 

enables new Everything-as-a-Service163 (XaaS) business models for the chip supply 

ecosystem. 

Cross-border chip traceability leveraging CHIPS Acts. In December 2022, the U.S.-

EU Technology Trade Council (TTC) officials agreed to strengthen chip supply chains164

by coordinating their CHIPS Acts strategies. Since then, TTC has gained significant 

allied nation support for partnerships and innovation, leading to $450 billion in 

government funds for fabs worldwide surpassing China’s $150 billion investment165. 

With 80% of global fab capacity controlled by allies, the U.S. and EU are well-positioned 

to pursue proven ecosystem strategies166 and pilot programs for global supply chain 

traceability like the National Defense Authorization Act (NDAA) applicable to US 

government purchases167. 

160 Executive Gov - NIST’s CHIPS R&D Office Intends to Create Digital Twin Manufacturing USA Institute 161 CNBC - How using analytics and AI can help companies manage the semiconductor supply chain 162 McKinsey & Company - Reimagining fabs: Advanced analytics in semiconductor manufacturing 163 Rochak Sethi, Deloitte - How Semiconductor Companies can leverage XaaS to drive value creation 164 WSJ - U.S., EU Agree to Coordinate Semiconductor Subsidy Programs 165 Sources: DARPA, EY.com GlobalFoundries, various business journals (estimated) 166 GSA TIES – Cybersecurity strategy to create a Digital Supply Chain Business Ecosystem 167 NDAA Sec. 5949 - Microelectronics traceability and diversification initiative
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The U.S. should lead supply chain traceability strategies by coordinating CHIPS Acts 

investments with the U.S.-EU TTC, USTR and NIST on key initiatives: 

1. Develop Standards Taxonomy: Utilize NIST’s worldwide reach with Standards 

Development Organizations (SDOs) to develop digital twins and lead in 

creating taxonomy of standards for supply chain traceability from chips to 

systems. 

2. Start Trusted Partnerships Network: Orchestrate multi-stakeholder Public 

Private Partnerships (PPPs) among EDA, IP, Chip Design, Foundry, OSAT 

vendors and tech hubs to create a digital infrastructure from design and 

manufacturing.

3. Invest in Pilot Projects to Prove Traceability Value: Fund cost-effective pilot 

projects with allied nations for collaboration to prove the economic value of 

digital infrastructure and the ability to deploy at scale with a small investment.

4. Accelerate Adoption and Cross-Border Digital Trust: Promote the U.S. Cyber 

Trust Mark168, the EU Digital Product Passport 169and CBP supply chain visibility 

pilots170 to enable a ‘digital paper trail’ and trusted digital marketplaces. 

Call to Action: We must act swiftly and leverage the U.S. and EU CHIPS Acts to create 

a traceability infrastructure that enables IoT Services and AI applications based on a 

Root of Trust embedded in chips during design and manufacturing. The investment 

is small, compared to the vast volume of chips produced by fabs over their lifecycle. 

Lack of action could result in dire consequences if adversaries control the Root of 

Trust. Conversely, embracing a trusted business ecosystem across chip supply chains 

will incentivize economic growth for the U.S., our allies, and potentially adversaries 

adhering to the trusted ecosystem policies. Section 4.3 covers the recommendations 

for this strategy.

168 whitehouse.gov - Biden-Harris Administration Announces Cybersecurity Labeling Program 169 World Business Counsil for Sustainable Development - The EU Digital Product Passport 170 cbp.gov - CBP Launches Global Business Identifier Pilot to Increase Supply Chain Visibility
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The U.S. should collaborate with allied nations on CHIPS Acts traceability strategy by 

orchestrating cross-border public private partnerships using IoT and AI technologies 

to trace and manage chips, fuel trusted digital marketplaces, bolster national security, 

and contribute trillions in global economies and our GDP. 

_________________
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Table of Abbreviations

(still being significantly updated)

AAM Advanced Air Mobility

ADPPA American Data Privacy and Protection Act

AI Artificial Intelligence

AIS Automated Indicator Sharing

APEC Asia-Pacific Economic Cooperation

AQ Air Quality

ASCE American Society of Civil Engineers

AASHTO American Association of State Highway and 

Transportation Officials

AV Automated vehicle

BABA Buy America, Build America

BIL Bipartisan Infrastructure Law

BIM Building Information Modeling

BX

CAGR

CCPA California Consumer Privacy Act

CESMII

CET Critical and Emerging Technologies

CIA Confidentiality and Integrity and Assurance

CIO

CISA Cybersecurity and Infrastructure Security Agency

CPA Colorado Privacy Act

CPAP

CPRA California Privacy Rights Act

CPS Cyber-Physical System

CTDPA

CV Connected Vehicle

DBOM Data IDs and Bills of Materials

DCS

DFAR Defense Federal Acquisition Regulation

DHHS Department of Health and Human Services

DL Deep learning

DoC Department of Commerce
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DoD Department of Defense

DOE Department of Energy

DOT Department of Transportation

EERE

EIA

EmT Emerging Technology

EPA Environmental Protection Agency

ERP Enterprise resource planning

EV Electric vehicles

FAA Federal Aviation Administration

FACA Federal Advisory Committee Act

FAR Federal Acquisition Regulation

FCC Federal Communications Commission

FDOT Florida Department of Transportation

FedVTE Federal Virtual Training Environment

FEM

FRM

FTC Federal Trade Commission

GCTC Global City Teams Challenge

GDPR General Data Protection Regulation

GIST Global Innovation through Science and Technology

GLS

GSA General Services Administration

HBOM

HIPAA

HVAC Heating, ventilation and air conditioning

IAM Identity and Access management

ID Information and data

IoMT Internet of Medical Things

IoT Internet of Things

IoTAB Internet of Things Advisory Board

IoTFWG Internet of Things Federal Working Group

IP Intellectual property

IRA Inflation Reduction Act

IT Information technology

ITU International Telecommunications Union

KEV Known Exploited Vulnerabilities

KPI Key performance indicators

LEO Low-earth orbit
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LPWAN Low Power Wide Area Networks

MBDA Minority Business Development Agency

MEP Manufacturing Extension Partnership

ML Machine learning

MVA Manufacture value added

NAAQS

NDAA

NEMA

NESHAP

NEVI

NHTSA National Highway Traffic Safety Administration

NICE National Initiative for Cybersecurity Education

NIETC National Interest Electric Transmission Corridors

NIST National Institute of Standards and Technology

NITRD

NOAA

NSF National Science Foundation

NSTC National Science and Technology Council

NTIA National Telecommunications and Information 

Administration

NVD National Vulnerability Database

O&M

ODM Original design manufacturers

OEM Original Equipment Manufacturers

OMB Office of Management and Budget

ONCD Office of the National Cyber Director

OSTP Office of Science and Technology Policy

OT Operational technology

PANDA

PbD Privacy by Design

PCAST President’s Council of Advisors on Science and Technology

PET Privacy-Enhancing Technologies

PHI

PID

PII Personally identifiable information

PoC Proof of Concept

PPDSA Privacy-Preserving Data Sharing and Analytics

PPE Personal protective equipment

PPP Public-private partnerships
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PQC Post quantum computing

PV

QC Quantum computing

RFID

RFP

ROI

RSR

SB Small and disadvantaged businesses

SBA

SBIR Small Business Innovation Research

SBOM

SCADA

SCSEP Smart City and Sustainability Extension Partnerships

SDO Standards Development Organizations

SENSOR

SMB

SME Small and medium enterprises

SSDF Secure Software Development Framework

STEM Science, technology, engineering, and mathematics

STTR Small Business Technology Transfer

THEA Tampa Hillsborough Expressway Authority

TMF Technology Modernization Fund

UAS

UF University of Florida

UI User interfaces

UNECE

USDA U.S. Department of Agriculture

USMCA United States-Mexico-Canada Agreement

USNSS

UX

VC

VOC
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Compliance Matrix

The IoTAB fulfills the role of the ‘‘steering committee’’ as established under subsection 

(b)(5)(A) of the NDAA Section. It supports the IoTFWG which is the working group 

convened under subsection (b)(1).

The IoTAB herein advises working group in the following areas:

Advisory Topic Relevant Report Sections

(i) the identification of any Federal 

regulations, statutes, grant practices, 

programs, budgetary or jurisdictional 

challenges, and other sector-specific 

policies that are inhibiting, or could inhibit, 

the development of the Internet of Things;

(ii) situations in which the use of the Internet 

of Things is likely to deliver significant and 

scalable economic and societal benefits to 

the United States, including benefits from or 

to

(I) smart traffic and transit technologies;

(II) augmented logistics and supply chains;

(III) sustainable infrastructure;

(IV) precision agriculture;

(V) environmental monitoring;

(VI) public safety; and

(VII) health care;

(iii) whether adequate spectrum is available 

to support the growing Internet of Things 

and what legal or regulatory barriers may 

exist to providing any spectrum needed in 

the future;

(iv) policies, programs, or multi-stakeholder 

activities that—
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Advisory Topic Relevant Report Sections

(I) promote or are related to the privacy of 

individuals who use or are affected by the 

Internet of Things;

(II) may enhance the security of the Internet 

of Things, including the security of critical 

infrastructure;

(III) may protect users of the Internet of 

Things; and

(IV) may encourage coordination among 

Federal agencies with jurisdiction over the 

Internet of Things;

(v) the opportunities and challenges 

associated with the use of Internet of Things 

technology by small businesses; and 

(vi) any international proceeding, 

international negotiation, or other 

international matter affecting the Internet 

of Things to which the United States is or 

should be a party.

[To be added before submission: The IoTAB is pleased to provide this report within the 

one year timeframe specified within the section. It represents independent advice (as 

specified in the NDAA) and represents the independent judgement of the steering 

committee, each member of which is acting as a stakeholder outside of the Federal 

Government with expertise relating to the Internet of Things.]