STEERING COMMITTEE FOR FOUNDATIONS 

FOR INNOVATION IN CYBER-PHYSICAL 

SYSTEMS

Th is report was prepared through the collaborative eff orts 

of the individuals noted below. It refl ects their expert 

contributions as well as the many insights generated at the 

Foundations for Innovation in Cyber-Physical Systems Workshop

held March 13-14, 2012 in Rosemont, Illinois.1

Committee Co-chairs

Janos Sztipanovits, Vanderbilt University

Susan Ying, Boeing

Steering Committee Members

Isaac Cohen, United Technologies Corporations

David Corman, Boeing

Jim Davis, UCLA and Smart Manufacturing Leadership 

Coalition

Himanshu Khurana, Honeywell Automation and Control 

Solutions 

Pieter J. Mosterman, MathWorks 

Venkatesh Prasad, Ford

Lonny Stormo, Medtronic, Inc.

1

 Workshop Report: Foundations for Innovation in Cyber-Physical Systems, January 

2013. http://events.energetics.com/NIST-CPSWorkshop/downloads.html

Th is report was prepared as an account of work cosponsored by the 

National Institute of Standards and Technology (NIST). Th e views and 

opinions expressed herein do not necessarily state or refl ect those of 

NIST. Certain commercial entities, equipment, or materials may be 

identifi ed in this document in order to illustrate a point or concept. 

Such identifi cation is not intended to imply recommendation or 

endorsement by NIST, nor is it intended to imply that the entities, 

materials, or equipment are necessarily the best available for the 

purpose.
Yiannis Aloimonos, University of Maryland, 

College Park

Carl Andersen, Federal Highway 

Administration

John Banting, Cooper Power Systems

Jay Bayne, Milwaukee Institute

Aaron Becker, University of Illinois, UrbanaChampaign

Patrick Beeson, Traclabs, Inc.

Aaron Bobick, Georgia Institute of Technology

Justin Bradley, University of Michigan

Brent Brunell, General Electric

Jason Burt, Bonneville Power Administration

David Chilin, University of California, Los 

Angeles

George Chiu, National Science Foundation

Isaac Cohen, United Technologies 

Corporation

Mike Coop, ThinkSmartGrid

David Corman, Boeing

Stephen Craven, University of Tennessee, 

Chattanooga

Joe D’Ambrosio, General Motors

Jim Davis, UCLA and Smart Manufacturing 

Leadership Coalition

Kent Donohue, UL LLC

Bruce Douglass, IBM

Sameh Elsharkawy, NiLogix, Inc.

Yaser P. Fallah, West Virginia University

Aydin Farajidavar, Georgia Institute of 

Technology

Kathleen Fisher, Defense Advanced Research 

Projects Agency

Tom Fuhrman, General Motors

Christopher Geyer, iRobot Corporation

Maysam Ghovanloo, Georgia Institute of 

Technology

Christopher Gill, Washington University in St. 

Louis

Helen Gill, National Science Foundation

Julian Goldman, Massachusetts General 

Hospital/Harvard Medical School

Bill Goodwine, University of Notre Dame

Chetan Gupta, HP Labs

Donny Helm, Oncor Electric Delivery

Naira Hovakimyan, University of Illinois, 

Urbana-Champaign

David Johnson, Boston Scienti

fi c

David Knowles, University of North Carolina, 

Chapel Hill

Heath LeBlanc, Vanderbilt University

Edward Lee, University of California, Berkeley

Hongwei Liao, University of Michigan

Taylor Lochrane, Federal Highway Administration

Amin Maghareh, Purdue University

Mary Ann Maher, SoftMEMS

Keith Marzullo, National Science Foundation

Eamonn McCormick, Alvarez and Marsal

Pieter J. Mosterman, MathWorks

Brian Murray, United Technologies Research Center

Necmiye Ozay, California Institute of Technology

Umit Ozguner, Ohio State University

Taskin Padir, Worcester Polytechnic Institute

Sai Prathyusha Peddi, The Ohio State University

Linh Thi Xuan Phan, University of Pennsylvania

Lee Pike, Galois, Inc.

Radha Poovendran, University of Washington

Leonard Radtke, Medtronic

Wenjing Rao, University of Illinois at Chicago

Luiz Rust Carmo, Inmetro Brazil

Bill Sanders, University of Illinois

Chaitanya Sankavaram, University of Connecticut

Shankar Sastry, University of California, Berkeley

A. Prasad Sistla, University of Illinois at Chicago

Jonathan Sprinkle, University of Arizona

Gaurav Srivastava, University at Buffalo

Anthony Star, Illinois Commerce Commission

Zhuoxiong Sun, Purdue University

James Swanson, University of Cincinnati

Janos Sztipanovits, Vanderbilt University

Burt Theurer, General Electric Global Research

David Vasko, Rockwell Automation

Ceeman Vellaithurai, Washington State University

Krishna Venkatasubramanian, University of 

Pennsylvania

Philip Wilsey, University of Cincinnati

Alexander Wyglinski, Worcester Polytechnic Institute

Mumu Xu, California Institute of Technology

Shahan Yang, University of Maryland

Susan Ying, Boeing

Justyna Zander, Harvard University, Simulated Way

Hongwei Zhang, Wayne State University

Feng Zhao, Microsoft Research-Asia

Lei Zhao, Purdue University

Yi Zhao, Futurewei

Hao Zheng, University of South Florida

CONTRIBUTORS

iii CONTRIBUTORS
iv
1CONTENTS

CONTENTS 

INTRODUCTION 2 

A Call to Action 3

Reaping the Benefits of Cyber-physical Systems 4

BROAD CHALLENGES FOR CYBERPHYSICAL SYSTEMS 6 

Scientific and Technical Challenges 6

Institutional, Societal, and Other Challenges 9

STRATEGIC R&D OPPORTUNITIES 12

SCIENCE AND ENGINEERING FOUNDATIONS 14

OPPORTUNITY 14

Robust, effective design and construction 

of systems and infrastructure

SYSTEM PERFORMANCE, QUALITY, AND ACCEPTANCE 17

OPPORTUNITY 17

Improved performance and quality assurance 

of computational and physical systems

SYSTEMS OF ENGINEERING 19

OPPORTUNITY 19

Effective and reliable system integration and interoperability 

WORKFORCE FOR CONTINUING INNOVATION 21

OPPORTUNITY 21

Dynamic, multi-disciplinary education and training 

CONCLUSION 22

REFERENCES 24
2INTRODUCTION

INTRODUCTION

Th e wide reach of the Internet along with rapid advances in 

miniaturization, speed, power, and mobility have led to the 

pervasive use of networking and information technologies (IT) 

across all economic sectors. Increasingly, these technologies are 

combined with elements of the physical world (e.g., machines, 

devices, structures) to create smart or intelligent systems that off er 

increased eff ectiveness, productivity, safety, and speed and enable 

functions not previously possible. 

Integrated networking, information processing, sensing and 

actuation capabilities allow physical devices to operate in changing 

environments. Th is makes smart systems possible but also creates 

the need for a new ‘systems science’ that can lead to unprecedented 

capabilities. Tightly coupled cyber and physical systems that 

exhibit this level of integrated intelligence are sometimes referred 

to as cyber-physical systems (CPS). All CPS have computational 

processes that interact with physical components. Th ese can be 

relatively simple (e.g., a heater, cutting machine) or comprise 

multiple components in complex assemblies (e.g., vehicles, aircraft 

systems, oil refi neries). Th e computational and physical processes 

of such systems are tightly interconnected and coordinated to work 

together eff ectively, often with humans in the loop. 

Robots, intelligent buildings, implantable medical devices, cars that 

drive themselves or planes that automatically fl y in a controlled 

airspace—these are all examples of CPS. Today, CPS can be 

found in such diverse industries as aerospace, automotive, energy, 

healthcare, manufacturing, infrastructure, consumer electronics, and 

communications. Everyday life is becoming increasingly dependent 

on these systems—in some cases with dramatic improvements. 

Th ere is a growing trend toward computational intelligence, 

automation, and control for complicated but well-defi ned tasks or 

processes, especially when demands or constraints are not amenable 

to human intervention. For example, automatic collision systems 

could detect moving objects and respond faster than a human 

operator. Unmanned CPS could be used to reduce the risk to 

human life by detecting mines, exploring volcanoes, or conducting 

otherwise hazardous tasks. Machines driven by a computer do not 

suff er fatigue and may be more precise than is humanly possible. In 

future CPS could make possible concepts only imagined today, such 

as unmanned tours to the moon, bionic suits, and automated largescale indoor agriculture systems.

This report is the third in a series of 

reports developed with input from 

a group of world-renowned experts 

in cyber-physical systems (CPS) 

and related technologies. The 

fi rst in the series is the Foundations 

for Innovation in Cyber-Physical 

Systems Workshop Report, which 

summarizes the results of a 

workshop held in March 2012 to 

gain broad views on the 

technology and measurement 

challenges limiting CPS. Second 

in the series is Strategic Vision and 

Business Drivers for 21st Century 

Cyber-Physical Systems, a report 

summarizing the ideas generated by 

a June 2012 Executive Roundtable. 

This event was attended by 

business and technical leaders in 

the fi eld representing a spectrum of 

applications for CPS, from medicine to 

energy to manufacturing. 

Building on previous reports, this 

document provides a high-level 

perspective of the key challenges and 

strategic research and development 

opportunities for advancing CPS. The 

report will be used by both public and 

private stakeholders to inform decisions 

about the technology R&D that should be 

pursued, as well as the new measurement 

methods and standards that must be 

developed to realize the transformative 

potential of CPS. 
3INTRODUCTION

Th is trend does not remove the importance of human involvement but does 

change roles and requirements for new skill sets. Furthermore, as CPS become 

more dependent on computational processes, it becomes increasingly important 

that they be engineered to be reliable, secure, and safe. Future scientifi c and 

engineering advances that extend the connectivity of these systems and deliver 

greater reliability could open new opportunities to take advantage of the unique 

properties of CPS. 

A CALL TO ACTION

Th e future applications of CPS are more transformative than the IT revolution of 

the past three decades. Unparalleled analytical capabilities, real-time networked 

information, and pervasive sensing, actuating, and computation are creating 

powerful opportunities for systems integration. Next generation CPS will be 

able to execute extraordinary tasks that are barely imagined today. Th ese new 

capabilities will require high-confi dence computing systems that can interact 

appropriately with humans and the physical world in dynamic environments and 

under unforeseen conditions. Achieving these capabilities presents a complex and 

multi-disciplinary engineering challenge.

Future CPS have many sophisticated, interconnected parts that must 

instantaneously exchange, parse, and act on detailed data in a highly coordinated 

manner. Continued advances in science and engineering will be necessary to 

enable advances in design and development of these complex systems. Multiscale, multi-layer, multi-domain, and multi-system integrated infrastructures 

will require new foundations in system science and engineering. Scientists with 

an understanding of otherwise physical systems will need to work in tandem 

with computer and information scientists to achieve eff ective, workable designs. 

Standards and protocols will be necessary to help ensure that all interfaces 

between components are both composable and interoperable, while behaving in 

a predictable, reliable way. 

Th is report is a call to action. It outlines a set of strategic R&D opportunities 

that must be addressed to enable advanced CPS to reach their potential and 

deliver broad societal benefi ts in the future. Th e United States (U.S.) is a global 

leader in cyber technologies and well-positioned to gain a competitive advantage 

in CPS. Work in CPS is moving rapidly forward on a global scale. In the 

European Union, the ARTEMIS program has proposed spending $7 billion on 

embedded systems and CPS by 2013—with a view to becoming a global leader 

in the fi eld by 2020. Japan is capitalizing on its traditional strengths in this fi eld 

to make technology advances, and currently hosts the largest tradeshow in the 

world on embedded systems. Th e great potential of CPS is motivating countries 

such as India and China to forge ahead into the fi eld. Th e opportunity is now for 

the U.S. to establish competitive leadership through the ability to develop next 

generation systems that you can trust your life with. 

“Advanced sensing, 

measurement, and 

process control, 

including cyberphysical systems...

has applicability 

across almost all 

industry domains. 

These technologies 

are critical for 

enhancing tradability...

megatrends of 

energy and resource 

effi ciency, better 

safety, and higher 

quality also depend 

highly on advances in 

sensing and automatic 

process control.”

Recommendation #2, 

Increase R&D Funding in 

Top Cross-cutting 

Technologies, from the 

Report to the President 

on Capturing Domestic 

Competitive Advantage in 

Advanced Manufacturing 

(PCAST, 2012) 
4INTRODUCTION

REAPING THE BENEFITS OF CYBERPHYSICAL SYSTEMS 

Development and use of advanced CPS will generate unique 

opportunities for economic growth, create skilled jobs for the long 

term, and help ensure the health, safety, and security of the nation 

while improving quality of life. CPS are drivers for innovation in a 

broad range of industries and can lead to new products or unlock 

new markets (see Table 1). By the end of the decade, embedded 

networking and computing components are projected to account 

for more than half of the value share in diverse sectors, including 

automotive, consumer electronics, avionics and aerospace, 

manufacturing, telecommunications, intelligent buildings, and 

health and medical equipment. A recent report estimates that 

the technical innovations of CPS could fi nd direct application 

in sectors currently accounting for more than $32.3 trillion in 

economic activity, and with the potential to grow to $82 trillion 

of output by 2025—about one half of the global economy (GE, 

2012).

U.S. manufacturing competitiveness will increasingly rely upon 

CPS technologies for advanced robotics and computer-controlled 

manufacturing processes linked to automated design tools, along 

with integrated, broad-based, and dynamic management of 

production lines, factories, and supply chains. Equally broadbased performance metrics will be needed to enable integration of 

economic, productivity, energy, and sustainability objectives. 

CPS are critical to national eff orts to reduce energy use while 

increasing performance, reliability, and effi ciency across economic 

sectors—via the smart grid, smart transportation systems, smart 

manufacturing, and smart buildings infrastructure. 

CPS is already facilitating a broad shift from hospital-based 

to home-based health care and expanding independent living 

opportunities for seniors. By extending the reach of quality 

care beyond traditional hospitals, CPS-based medical devices 

and systems are enabling more individualized health care and 

improved patient outcomes. As advances are made, CPS can lead 

to new capabilities to diagnose, treat, and prevent disease. 

In national defense, CPS now delivers superiority in virtually 

all weapons systems, including manned and unmanned aircraft, 

ground vehicles, robotic platforms, surface and underwater vessels, 

and the overarching systems that integrate the nation’s fi ghting 

forces. In homeland security and law enforcement, CPS is used in 

diverse roles from bomb disposal and emergency response 

robotics to sensor networks providing advance warning of 

catastrophic events. 
5INTRODUCTION

TABLE 1. APPLICATIONS OF CYBER-PHYSICAL SYSTEMS

Innovative Products 

or Applications Cyber-Physical Systems Impacts

Smart Manufacturing and Production

• Agile manufacturing

• Supply chain connectivity

• Intelligent controls

• Process and assembly automation

• Robotics working safely with humans

• Enhanced global competitiveness 

• U.S.-based high tech manufacturing 

• Greater effi ciency, agility, and reliability

Transportation and Mobility

• Autonomous or smart vehicles (surface, air, 

water, and space)

• Vehicle-to-vehicle and vehicle-toinfrastructure communication 

• Drive by wire vehicle systems 

• Plug ins and smart cars

• Interactive traffi c control systems 

• Next-generation air transport control

• Accident prevention and congestion 

reduction (zero-fatality highways)

• Greater safety and convenience of travel

Energy

• Electricity systems

• Renewable energy supply

• Oil and gas production

• Smart electric power grid 

• Plug-in vehicle charging systems

• Smart oil and gas distribution grid 

• Greater reliability, security, and diversity of 

energy supply

• Increased energy effi ciency

Civil Infrastructure

• Bridges and dams

• Municipal water and wastewater treatment

• Active monitoring and control system

• Smart grids for water and wastewater 

• Early warning systems

• More safe, secure, and reliable infrastructure

• Assurance of water quality and supply

• Accident warning and prevention

Healthcare

• Medical devices

• Personal care equipment 

• Disease diagnosis and prevention

• Wireless body area networks

• Assistive healthcare systems 

• Wearable sensors and implantable devices

• Improved outcomes and quality of life

• Cost-eff ective healthcare

• Timely disease diagnosis and prevention

Buildings and Structures

• High performance residential and 

commercial buildings 

• Net-zero energy buildings 

• Appliances 

• Whole building controls

• Smart HVAC equipment

• Building automation systems

• Networked appliance systems 

• Increased building effi ciency, comfort and 

convenience

• Improved occupant health and safety

• Control of indoor air quality

Defense

• Soldier equipment

• Weapons and weapons platforms 

• Supply equipment

• Autonomous and smart underwater sensors 

• Smart (precision-guided) weapons 

• Wearable computing/sensing uniforms

• Intelligent, unmanned vehicles

• Supply chain and logistics systems 

• Increased warfi ghter eff ectiveness, security, 

and agility 

• Decreased exposure for human warfi ghters 

and greater capability for remote warfare

Emergency Response

• First responder equipment

• Communications equipment

• Fire-fi ghting equipment

• Detection and surveillance systems 

• Resilient communications networks

• Integrated emergency response systems 

• Increased emergency responder 

eff ectiveness, safety, effi ciency, and agility

• Rapid ability to respond to natural and 

other disasters 
6BROAD CHALLENGES FOR CYBER-PHYSICAL SYSTEMS

BROAD 

CHALLENGES 

FOR CYBERPHYSICAL 

SYSTEMS Th e interconnection of networking, computing, physical, and 

human components reaches most engineered systems and 

yields revolutionary new capabilities. Th e underlying technical 

challenges also have a great deal of commonality refl ecting a 

range of fundamental scientifi c, engineering, institutional, and 

societal issues. Barriers arise throughout all stages of technology 

development, from basic science through applied R&D, 

demonstration, manufacturing, and deployment. Addressing the 

most critical of these will help ensure that in the future CPS are 

reliable, safe, producible, and secure. 

SCIENTIFIC AND TECHNICAL CHALLENGES

Advancement in CPS requires a new systems science that 

encompasses both physical and computational aspects. Systems 

and computer science has provided a solid foundation for 

spectacular progress in engineering and information technology; 

a type of new systems science is now needed to address the unique 

scientifi c and technical challenges of CPS. 

Integrating complex, heterogeneous large-scale 

systems. Future CPS will contain heterogeneous distributed 

components and systems of large numbers that must work 

together effectively to deliver expected performance. There are 

several challenges to achieving this today. A fundamental issue is 

the lack of common terminology, modeling languages, and 

rigorous semantics for describing interactions—physical and 

computational—across heterogeneous systems. Achieving the 

interoperability and compositionality of various components 

constructed in different engineering domains and sectors, without 

the benefi t of unifying theories and standards, presents a major 

challenge. A lack of clear ownership of the interface between 

systems (e.g., between code, hardware, and multiple equipment 

vendors) also contributes to interoperability and integration 
7BROAD CHALLENGES FOR CYBER-PHYSICAL SYSTEMS

problems. In addition to standards, interoperable systems 

need to ensure that timely outputs, outcome agreements, 

resilience, data transfers, and technical security protocols 

are addressed seamlessly within and between components. 

This includes aggregating and sharing data within systems 

as well as across systems and components. 

Interaction between humans and systems. 

Current models for human and machine behaviors are 

not adequate for designing CPS when humans and 

machines closely interact. One of the challenges is modeling and measuring situational awareness—human perception of the system and its environment and changes in 

parameters that are critical to decision-making. This is 

particularly necessary for complex, dynamic systems, such 

as those used in aviation, air traffi c control, power plant 

operations, military command and control, and emergency services. In such systems situational awareness can 

involve large and unpredictable combinations of human 

and machine behavior. Inadequate situational awareness and limited ability to model the human component 

in large complex systems has been identifi ed as one of 

the primary factors in accidents related to human error 

(Nullmeyer et al, 2005).

Dealing with uncertainty. Complex CPS need 

to be able to evolve and operate reliably in new and 

uncertain environments. An increasing number of these 

systems will also demonstrate emergent and unknown 

behaviors as they become more and more reliant on machine learning methodologies. In both cases, uncertainty 

in the knowledge or outcome of a process will require 

new ways to quantify uncertainty during the CPS design 

and development stages. Current methods for characterization and quantifi cation of uncertainty are limited and 

inadequate. This is exacerbated by the limits of reliability 

and accuracy of physical components, the validity of 

models characterizing them, network connections, and 

potential design errors in software. Ongoing debate also 

surrounds the expectations for quantifying uncertainty, 

that is, attaining perfect results given the uncertainty of 

the physical world and approximations in design. 

Measuring and verifying system 

performance. The diffi culty of verifying 

performance, accuracy, reliability, security, and various 

other requirements impedes development and investment 

in CPS. Today’s capabilities for verifi cation and validation (V&V) of CPS are limited, time consuming, and 

costly, particularly when compared to development time. 

Two major challenges are the creation of methodologies 

to further the capabilities of V&V of complex systems, 

and the development of test beds and datasets to support 

a principled approach to the validation of complex CPS. 

If the design phase is more reliable, testing can become 

more informed and require less time. The evaluation 

challenges will become increasingly diffi cult at the larger 

scales and higher complexity expected for future CPS, 

which will have massive and interconnected sensor, actuator, and component networks. 

7BROAD CHALLENGES FOR CYBER-PHYSICAL SYSTEMS

Robots can be designed to accomplish tasks that were not possible 

before. At left, researchers at the National Renewable Energy 

laboratory are using new robots to fabricate and analyze thinfi lm solar photovoltaic cells with greater precision and speed 

than ever before possible. When working with silicon, the robot 

can build a semi-conductor on a six-inch-square plate in about 

35 minutes—while analyzing anomalies and light absorption and 

preparing the next plates. The robot is able to complete tasks that 

previously required as many as fi ve laboratories. 

Credit: NREL 17161/Pat Corkery (NREL, 2010)
8BROAD CHALLENGES FOR CYBER-PHYSICAL SYSTEMS

Metrics are essential for the evaluation of many aspects of CPS, 

from design to testing, deployment, and operation. Key areas 

where scientifi cally-based metrics are needed include complexity, adaptability, safety, security, privacy, resilience, reliability, and 

manufacturability. One major challenge is to design metrics with 

suffi cient fl exibility to be applicable to a wide variety of systems. 

Determining how to use metrics effectively presents another challenge. For example, if metrics for privacy are defi ned, then design 

methods for achieving privacy objectives must also be developed. 

There are also challenges in modeling privacy requirements so 

that a system can be validated against these requirements.

System design. The design of CPS is hampered by the 

limited ability to design at a systems-level. There are many factors impeding system-level design, such as the lack of formalized high fi delity models for large systems, insuffi cient ways of 

measuring performance, and inadequate scientifi c foundations 

(e.g., no ‘science of systems’). A key factor is compositionality2

and modularity in the design approach. Compositionality in 

CPS is impacted by the strong interdependencies of software and 

systems engineering and often limited by poor system design. 

For example, CPS development could be greatly facilitated if 

system components could be developed and verifi ed in isolation 

and the system-level properties inferred from the properties of 

its parts. Designers of CPS aspire to this modular and compositional approach both in design and verifi cation. However, it is 

only currently possible in narrow domains and with restricted, 

simple properties. Scientifi c and technical challenges to achieving compositionality include a lack of mathematical and system 

science foundations, formalized metrics, evaluation techniques, 

and methods for dealing with cross-cutting properties in the design space. Furthering the mathematical methodology for design 

space exploration is critical for allowing a principled approach to 

design complex architectures that are modular. 2

 Compositionality in this sense means that system-level properties or 

performance can be derived from the local properties of individual 

components.
9BROAD CHALLENGES FOR CYBER-PHYSICAL SYSTEMS

INSTITUTIONAL, 

SOCIETAL, AND OTHER 

CHALLENGES

Trust, security, and privacy. 

Assuring that systems are trustworthy, secure, and protect the privacy of 

information creates both technical and 

policy challenges. Cyber-security is a 

critical aspect of CPS on many levels, 

including the protection of national 

infrastructure, privacy of individuals, 

system integrity, and intellectual property. Recent foreign-based intrusions 

on U.S. computer systems, both government and commercial, illustrate the 

current vulnerabilities of the Internet 

and the rationale for addressing the 

global security of cyberspace (GAO, 

2010). While cyber-security is a strong 

national priority and much progress 

has been made to ensure protection 

from cyber-attacks, CPS security raises 

a host of new challenges. For example, 

the combination of cyber and physical vulnerabilities may lead to attack 

models that are fundamentally new, 

hard to analyze, and carry substantial 

risk in maintaining physical integrity 

of critical systems. 

Challenges to secure CPS include 

modeling the security threat, developing a formal approach to CPS vulnerability assessments, and designing 

evolutionary and resilient architectures 

to handle rapidly evolving cyber and 

physical threats. Along with security, 

maintaining privacy and confi dentiality is an important aspect. Patients depending on implanted medical devices, 

for example, want protection of their 

identity and critical health information 

that could be exposed via the connection of their devices to monitoring 

networks. Industry requires protection of intellectual property as well as 

sensitive business and demographic 

information. Assuring the confi dentiality of information and controlling the 

access and use of data are challenging, 

especially as the systems that collect, 

manage, and analyze information are 

rapidly evolving and in some cases 

need to operate in a distributed or relatively open environment. 

Effective models of 

governance. The rapidly emerging global networks of CPS in energy, 

air traffi c, transportation, cloud-based 

services and many others call for new 

governance models—both domestic 

and global—for providing standards, 

protocols, and oversight of systems 

that operate both in physical and cyber 

space. These new governance models 

are being explored but are not yet 

formalized. Governance could provide 

structured control and regulation for 

these systems and reduce liabilities that 

arise because of unwanted intrusions 

or other vulnerabilities. Governance is 

being discussed in many organizations, 

ranging from expert forums to treatybased, decision-making bodies within 

governments. There is growing debate 

around these issues, with some pushing for increased intergovernmental 

oversight while others contend that 

the private sector can self-regulate via 

development of appropriate economic 

incentives, rules, and controls. 

Many factories have 

robots as well as 

humans working in 

them; but the two 

do not always work 

well together. At the 

Massachussets Institute 

of Technology (MIT), 

researchers have come 

up with an algorithm 

that may make it easier 

and safer for humans 

and robots to work 

side-by-side, giving 

robots the tools to learn 

the preferences of a 

human coworker. 

(MIT, 2012)
10BROAD CHALLENGES FOR CYBER-PHYSICAL SYSTEMS

Creation of CPS business models. The extreme 

systems integration inherent in CPS is a disruptive technology 

that changes the status quo, creates new industries, and eliminates 

others. Transformation of traditional industries into those that 

are CPS-based is a complex, high risk process because it requires 

fusing the business models of the IT industry with those of 

engineering-based industries. These fused business models are not 

yet well-established and can be diffi cult to convey. A contributing 

factor is that economic and other data that could be used to support a business case are not well documented for CPS. The lack of 

a generic, proven business model can inhibit investments in new 

technologies and systems, in spite of the benefi ts. 

Today’s examples of successful CPS business models include the 

aviation industry, which has incorporated cyber-physical avionic 

systems in modern airplanes. In this case, the industry understands the safety implications and has developed stringent safety 

standards and certifi cation processes. As CPS become larger and 

more complex, the issues of business risk and liability also increase. 

There is an opportunity to mitigate this risk by sharing the cost of 

developing precompetitive and infrastructure technologies.

Understanding the value of CPS. CPS will benefi t from 

well-developed infrastructure, which requires signifi cant upfront 

investment. The value of CPS needs to be better understood for 

such investments to occur. R&D on CPS is often described in 

terms that are theoretical or include vocabulary that is not readily 

recognized. As a result, understanding the substance and applying the results of CPS R&D can be challenging for businesses, 

decision-makers, and end-users. Less academic and more strategically insightful ways of presenting CPS research, benefi ts, and risks 

would facilitate quicker and less expensive industry adoption of 

emerging technologies as well as improved understanding of the 

benefi ts and applications of CPS research. Some studies have presented methods to successfully articulate the value of CPS-related 

technology (BAH, 2010) but overall this remains a challenge. 
11BROAD CHALLENGES FOR CYBER-PHYSICAL SYSTEMS

Multi-disciplinary education and collaboration. The science and engineering of CPS are crossdisciplinary in nature, requiring expertise in computer 

science, mathematics, statistics, engineering, and the 

full spectrum of physical sciences—even extending into 

the arts such as ethics and psychology. Working across 

disciplines can be challenging, as it requires experts with 

highly diverse backgrounds to communicate on a common basis. In academia, there is a lack of concentrated, 

multi-disciplinary CPS education and research, as efforts 

have focused on the cyber or physical domains rather 

than a combination of the two. Signifi cant challenges 

exist in creating multi-disciplinary CPS programs within 

the existing university structure, which has historically 

been divided into conventional disciplines (e.g., computer 

science, engineering, chemistry). Academia has previously 

confronted and successfully addressed similar challenges, 

resulting in the creation of new, vibrant industries such as 

bio-engineering.

Skilled workforce. CPS are sophisticated, advanced 

technology systems that require knowledge and training 

to design, develop, implement, and use. They require new 

skills and a new workforce. Creating and maintaining a 

skilled workforce to support future CPS is a signifi cant 

challenge in its own right. CPS technology is a rapidly 

changing fi eld and mechanisms for training and continuing education will be needed, as well as qualifi ed instructors that stay abreast of emerging developments. Rigorous 

tools for workforce training in CPS are not currently 

available but could be highly effective in creating and 

maintaining a future workforce. 

11

Research programs in CPS across the nation are leading to new 

discoveries and technologies while helping to educate a multidisciplinary future workforce. A considerable portion of this 

research is conducted through U.S. government programs. 

For example, at the National Science Foundation (NSF) the 

CPS program provides support to universities to develop the 

core system science needed to engineer complex cyberphysical systems and fosters a research community committed 

to advancing research and education in CPS. At the Defense 

Advanced Research Projects Agency (DARPA), research is ongoing 

in several areas that will accelerate progress in CPS. These include adaptive vehicles, 

construction of high-assurance cyber-physical systems, and advanced model-based 

design methods for cyber-physical systems. Within agencies, research in CPS is underway 

on mission-oriented applications, such as the smart grid, intelligent buildings, and 

advanced medical devices. The activities in CPS across federal agencies are coordinated 

by the Networking and Information Technology R&D (NITRD) Senior Steering Group on CPS 

and the High Confi dence Software and Systems Coordinating Group. This group fosters 

close communication and liaison among agencies, academia, and industry to address 

CPS R&D needs and facilitate interagency program planning in this fi eld.
12STRATEGIC OPPORTUNITIES

STRATEGIC R&D 

OPPORTUNITIES

A number of strategic R&D opportunities have been identifi ed 

as critical to accelerating progress in CPS and overcoming some 

of the important challenges. Th ese are illustrated in Table 2 and 

described in depth on the following pages. Th ey cover the full 

spectrum of CPS design, development, implementation, and use, 

including:

• Science and engineering foundations

• System performance, quality, and acceptance

• Applied development and deployment

• Workforce for continuing innovation in CPS

Measurement science and technology advances are woven 

throughout these opportunities and impact all stages of CPS 

development, from fundamental science and discovery to 

commercialization and deployment. For example, the major 

challenges of interoperability, interactions between humans 

and machines, understanding uncertainty, and evaluating 

performance all have strong roots in measurement science 

and technology. Th e strategic R&D opportunities are recurring themes that 

appear in multiple technology areas and consequently would 

have far-reaching impact if addressed. Th ey represent the priority 

research that has been identifi ed as essential to advancing the 

state of CPS and reaping the potential benefi ts to society and 

the nation. 
13STRATEGIC OPPORTUNITIES

TABLE 2. STRATEGIC R&D OPPORTUNITIES FOR CYBER-PHYSICAL SYSTEMS

Robust, Effective Design and Construction of Systems and Infrastructure

Science and 

Engineering 

Foundations

Develop cost-eff ective system design, analysis, and construction 

Create domain-specifi c frameworks for design

Manage the role of time and synchronization in architecture design

Enable natural, more seamless human-CPS interactions

Develop systematic inter-process and inter-personal communication for sensors and actuators

Improved Performance and Quality Assurance of Computational and Physical Systems

System 

Engineering

Create methods for system-level evaluation, verifi cation, and validation of cyber-physical systems 

Develop science-based metrics (e.g., security, privacy, safety, resilience, adaptability, fl exibility, reusability, 

dependability)

Eff ectively characterize and quantify reliability amidst uncertainties

Effective and Reliable System Integration and Interoperability Applied 

Development 

and 

Deployment

Create universal defi nitions for representing ultra-large heterogeneous systems

Build an inter-connected and interoperable shared development infrastructure

Develop abstraction infrastructure to bridge digital and physical system components

Dynamic, Multi-Disciplinary Education and Training Workforce for 

Continuing 

Innovation in 

CPS

Establish multi-disciplinary CPS degrees and resources 

Pursue dynamic training and certifi cation in CPS 
14STRATEGIC OPPORTUNITIES

SCIENCE AND ENGINEERING 

FOUNDATIONS OPPORTUNITY

Robust, effective design and construction of systems and 

infrastructure

The development of CPS requires a new systems science foundation 

that can effectively integrate the elements of complex computational 

systems and processes with physical systems. Building blocks for design 

involve modeling, synthesis, simulation, and verifi cation capabilities, 

new design tools and frameworks, ontologies and modeling languages 

that cross discipline boundaries, methods that enable scalability from 

concept to operation, and the means to ensure a range of functional, 

performance, safety, security, and reliability requirements. 

Develop cost-effective system design, analysis, and 

construction methods

—Before making large investments 

in a prototype CPS, it is important for designers to create a 

model to understand the dynamics of the many subsystems 

and their interactions, including the environment in which the 

deployed system must operate. Approaches are needed to develop 

models that are robust, semantically precise, reduce design and 

verifi cation costs, and are reusable assets. 

Today, building formalized, high fi delity models using 

mathematically based, formalized modeling languages is 

expensive, time consuming, and lacking tools and methods for 

large heterogeneous systems such as CPS. Such models should 

include an appropriate level of abstraction for the properties 

relevant to the system being designed, and be able to simulate 

system behavior under a range of conditions and assumptions. 

New, formal modeling methods are needed to create robust, 

physically relevant simulations that accurately recreate scenarios 

that CPS systems will experience in operation. 

Creating more detailed models based on fi rst principles is 

desirable but increases the number of parameters that must be 

estimated for model calibration—and the measurements required 

to fi t these parameters can be diffi cult to obtain. Methods will be 

needed to recognize dominant parameters and apply abstractions 

to remove those that are less relevant from the model. For CPS 

this is especially important in developing models that are useful 

for studies at the systems level. Such models would evidence the 

phenomenological behaviors that emerge from the detailed fi rst 

principles but balance abstraction and approximation, while 

characterizing these in light of the purpose they serve in system 

design.
15STRATEGIC OPPORTUNITIES

Th e development and broad 

application of rigorous modeling tools 

could reduce the cost and duration of 

the design process, while improving 

design quality, performance, resilience, 

and dependability. Ultimately, 

domain-specifi c CPS design tools 

are required for aerospace, defense, 

transportation, medicine, and 

other industries that are built on 

standardized, confi gurable, and 

reusable tool suites for safety-critical 

and high-reliability systems. 

In addition to system modeling, 

major challenges include designing 

to confl icting requirements of system 

components (which can cause 

unintended consequences), a lack of 

tools or framework for co-designing 

heterogeneous components and 

systems, a lack of design standards 

to enable interoperability, and 

a lack of foundations to enable 

compositionality. Co-design is a 

particularly critical factor in the 

development of systems that face 

extreme demands and require high 

levels of performance, safety and 

reliability. Interoperability is a 

challenge that is exacerbated in CPS 

where there are large, complex, highly 

networked systems and components 

originating from multiple domains 

and disciplines. 

Create domain-specifi c frameworks 

for design—Engineering methods 

for co-design and new standards are 

needed that off er a common semantic 

foundation for modeling languages 

for exchange and translation across 

domains. Creating domain-specifi c 

design frameworks that are built on 

generic but customizable methods and 

tools would contribute substantially to 

reducing time to market, development 

costs, and the complexity of the 

design process. Finally, the design and 

implementation of CPS needs to be 

understood as a process that includes 

not only evaluation and co-design, 

but incorporates the ability to build 

sophistication as the levels of need 

advance. 

Manage the role of time and 

synchronization in architecture 

design—Management of time and 

synchronization is a complex yet 

critical issue for real-time CPS. 

Generally speaking, synchronization 

is the coordination of events that 

must occur to operate a system and 

the coordination of time between 

the cyber and physical dimensions 

of CPS. In computer science, for 

example, synchronization refers to the 

coordination of simultaneous threads 

or processes to complete a task. With a 

mobile device, synchronization occurs 

when the device communicates with 

applications on a personal computer 

or server (e.g., syncing or docking 

the device). For a vehicle system or 

manufacturing unit, time management 

occurs in reference to physical 

processes that have actual physical 

consequences. Today, timekeeping 

technologies such as Global 

Positioning System satellites and the 

Network Time Protocol provide realtime approximation of Coordinated 

Universal Time (world time standard) 

and are used for many synchronization 

applications. 

Poor timing and synchronization 

can result in data loss, downtime, 

and performance failure. Major 

challenges include eff ective timing 

and synchronization of multiple tasks, 

developing a unifi ed, common view of 

time, measuring time and time scales, 

Standards for 

Autonomous 

Vehicles

3D measurement of 

overhanging obstacles 

in the path of an AGV or 

industrial vehicle 

Credit: NIST

There is a growing 

acceptance of 

either partially or 

fully autonomous 

mobile equipment in 

the manufacturing 

area. However,in 

manufacturing facilities 

people and mobile 

equipment frequently 

move through the 

same cluttered and 

constantly-changing 

environment. 

Standards are 

essential to reduce 

the potential for 

injury and ensure a 

safe environment. 

The ability to control 

multiple autonomous 

vehicles from 

different 

manufacturers with 

different sensing 

capabilities is also 

a challenge. 
16STRATEGIC OPPORTUNITIES

and communicating time characteristics to system components 

or sensors. Overcoming these challenges could impact any 

data driven, real-time application. Simply put, eff ective time 

management will make it easier for applications to run in a 

time-correct manner. Tackling these challenges may require 

multi-layered architecture for time management.

Enable natural, more seamless human-CPS interactions—A 

better model of human strengths and weaknesses and the 

corresponding machine strengths and weaknesses is needed 

to create a more natural, seamless interaction between 

humans and CPS. Models that are adaptive, implementable 

at varying degrees of sophistication, and optimized for human 

interventions will help manage risks and safety as systems 

move toward mixed-initiative modes of operation. Th ey could 

also make humans more comfortable with and accepting of 

machine interactions. 

Cognitive models are needed for human-machine behavior 

that can be validated and become adaptable to interactions as 

they occur. Cognitive models should also consider the growing 

number of autonomous CPS and that human-machine 

interactions are increasingly participatory. Th e requirement to 

couple unpredictable human behavior with the predictable, 

hard-wired behavior of machines and physical systems creates 

inherent diffi culties in developing such models. 

Develop systematic inter-process and interpersonal 

communication for sensors and actuators

—A core 

component of CPS is the interpretation of data from various 

sources. CPS can contain highly connected and massive 

networks of sensors, actuators, and other devices that collect 

and act on many types of data. It is inherently diffi cult to 

measure the behavior of complex systems that contain multiple 

pathways for data interpretation, planning, and control. Th e need to measure human interactions adds another level of 

complexity and uncertainty. A structured design and process 

integration method is needed to systematically relate multiple 

signals and symbols for inter-process and interpersonal 

communications across domains and applications. Th is would 

enable the development of less expensive plug-and-play sensors, 

create opportunities for modular, plug-and-play CPS, and lead 

to structured design and integration tools that reduce the cost 

and time to market of new systems. 
17STRATEGIC OPPORTUNITIES

SYSTEM PERFORMANCE, QUALITY, 

AND ACCEPTANCE

OPPORTUNITY

Improved performance and quality assurance of 

computational and physical systems

Development and acceptance of CPS in real-world 

applications will require assurances that these systems 

will perform as expected. Assessing both performance and 

quality involves V&V of the functioning of the entire 

system as well as individual components. The ability to 

infer the performance and quality of the entire system from 

its components can be advantageous—a property that is 

often referred to as compositionality—but is challenging 

to achieve in practice.The ability to compare performance 

and quality consistently across systems is essential but will 

require standardized, science-based metrics for safety, security, 

resilience, and other key parameters. Predicting operational 

performance and quality characteristics of CPS with high 

confi dence (i.e., quantifi ed assessment) is especially important 

for systems that operate autonomously or that directly impact 

human health and safety. 

Create methods for system-level evaluation, 

verifi cation, and validation of CPS—Evaluating 

the performance of CPS against system requirements 

is needed to facilitate acceptance, investment, and 

practical use of these systems. Some classes of CPS will 

require extensive and sustained investment (e.g., smart 

transportation, smart grid) and a solid understanding 

of potential performance to move technologies forward. 

System-level evaluation can be performed with V&V 

methods, especially for safety and trustworthiness 

requirements, but without standardized requirements, 

V&V is customized and costly. V&V is also challenged by 

an inability to eff ectively evaluate the whole system (how 

well components work in concert) since the performance 

of individual components (i.e., cyber, physical, and 

cyber-physical assemblies) does not necessarily translate 

to overall system performance. Th e diffi culty of 

evaluating integrated components which interact in 

multiple temporal, spatial, and power scales also adds to 

the challenge. Cost eff ective methods of verifying and 

validating CPS could help decrease the cost of system 

integration, while increasing system reliability. 

Foundations and infrastructure are currently lacking for 

evaluation and V&V of emerging CPS, but could be 

developed by leveraging methods and tools already in use 

in other systems. An integrated approach will be needed 

to enable greater understanding of the interactions 

between components, the role and impact of interfaces, 

and emerging system properties. 

Autonomously operating systems (those with little human 

interaction or decision making) require certifi cation 

processes that attest to assured system performance. 

Certifi cation is a judgment that a system is adequately 

safe, secure, or meets other criteria for a given application 

in a set environment. To be valid, this judgment should 

be based on as much explicit and credible evidence as 

possible, with a foundation in good metrics including 

ways to measure complexity. 

However, certifi cation of complex, heterogeneous systems 

is extremely diffi cult, particularly in the design phase. 

Currently, system architecture, design, integration, 

and design space exploration are only robust enough 

to allow for building systems fi rst, then testing and 

certifying. A challenge is to create methodology to enable 

compositional certifi cation, which includes certifi cation 

of components separately without the need for recertifying after the system components are integrated. 

The U.S. Department of Transportation (DOT) is exploring use of 

short-range communication in “smart” cars to improve vehicle 

safety. Intersection-connected vehicles can improve safety at 

busy intersections.

Credit: U.S. Department of Transportation
5

 In computer science, abstraction is the process by which data and programs 

are defi ned with a representation similar in form to its meaning (semantics), 

while hiding away the implementation details. Abstraction tries to reduce and 

factor out details so that the programmer can focus on a few concepts at a 

time. A system can have several abstraction layers whereby diff erent meanings 

and amounts of detail are exposed to the programmer. 6 18 http://chess.eecs.berkeley.edu/pubs/427/Lee_CyberPhysical_ISORC.pdf STRATEGIC OPPORTUNITIES

Another challenge is integrating design artifacts and analyses as 

evidence (including partial and historic) into the certifi cation 

process.

Develop science-based metrics for system qualities (e.g., 

security, privacy, safety, resilience, adaptability, fl exibility, 

reusability, dependability)

—A universal set of science-based 

metrics is needed to evaluate and predict how CPS will perform 

with respect to key system-level properties such as security, 

privacy, safety, resiliency, and dependability. Dependability in 

this case means that a system is highly reliable when running, 

but also capable of eff ectively predicting, recognizing, and 

quickly covering from unforeseen events. While it is technically 

challenging to develop scientifi cally-based measurements for 

these broad concepts, they are fundamental to developing and 

deploying dependable CPS. 

Metrics are needed for all phases of CPS development, from 

the early design stages through prototype, testing, deployment, 

operation, and operation regimes (e.g., before and after system 

changes or failures). Design-phase metrics will enable engineers 

to build in safety, resilience, and dependability in the early stages 

of development. During the testing stage, metrics can help 

confi rm that prototypes exhibit the desired characteristics. In 

deployment and operation, metrics can measure and monitor 

system behavior and provide indications of emerging issues. Th e 

use of science-based metrics will lead to greater system reliability 

and safety, and allow for fewer, lower-impact failures. Metrics 

could also be formulated to specify a minimum level of reliability 

and a maximum level of uncertainty. Metrics are also essential 

to supporting business models and investment because they will 

enable clear defi nition of questions of liability.

Effectively characterize and quantify reliability amidst 

uncertainties—Reliable CPS must behave with some degree 

of certainty, even in a dynamic, unpredictable environment. 

Characterization and quantifi cation of reliability provides 

information on how a system responds to expected and 

unexpected events, and aids in understanding the potential risks 

to system operation. The numerous heterogeneous components, 

disparate characteristics of the physical versus cyber elements, 

and operational uncertainties found in CPS complicate the 

characterization of reliability. Failures could occur in both cyber 

and physical components and affect other system components in 

complex ways. For example, multiple car accidents experienced 

by a smart traffi c control system could unexpectedly overload 

the information processing capacity and its ability to respond in 

real time.
19STRATEGIC OPPORTUNITIES

Today, formal methods for 

determining reliability are lacking for 

most CPS and need to be developed. 

Such methods should be able to 

adapt to changing inputs, be able 

to compose disparate systems, and 

provide reproducible results. Effective 

characterization and quantifi cation of 

reliability will ensure that systems are 

robust and resilient, and provide better 

understanding of potential risks to 

system operation. 

SYSTEMS OF 

ENGINEERING

OPPORTUNITY

Effective and reliable system 

integration and interoperability

A unique characteristic of CPS is 

that they integrate computing and 

communication capabilities in the 

sensing and actuation functions of 

multiple components in the physical 

world. For CPS to operate dependably, 

safely, securely, effi ciently, and in real 

time, some if not all components, 

whether cyber or physical, must be able 

to interact and communicate. These 

tightly coupled interactions require a 

high level of system integration and 

interoperability. System interfaces must 

be compatible and interactions should be 

governed by well-defi ned specifi cations; 

simulations of these interfaces should 

also use semantically precise modeling 

languages and vocabularies. In addition, 

individual components, as well as the 

total system, must be able to interact 

seamlessly with and respond to human 

operators and interventions. 

Create universal defi nitions 

for representing ultra-large 

heterogeneous systems—Standard 

methods and shared conceptualization 

are needed for aligning the description 

of large, heterogeneous groups of 

system components, characteristic of 

many CPS, including specifi cations 

for technology, human elements, 

time, and space. Standard methods 

should include ways to universally 

and visually represent overall system 

behavior and performance of the 

integrated components. Th e objective 

of shared conceptualization is to 

provide standard defi nitions and/

or ways for readily translating or 

mapping between systems that can be 

embraced by both industry users and 

suppliers of technologies and subsystems. Developing agreements and 

methods to align CPS is complicated 

by the heterogeneity and disciplinary 

isolation of vocabularies and modeling 

languages for diff erent aspects of large, 

heterogeneous systems. Challenges 

include an inability to measure the 

presence and correctness of complete 

system requirements and behavior of 

components within the context of the 

overall system. Th e key parameters 

that need to be universally defi ned 

must also be identifi ed; this will 

require cross-disciplinary interactions 

among the cyber and physical 

sciences communities. If successfully 

developed, a consistent set of 

defi nitions could lower currently high 

integration and development costs, 

and provide a means to clarify top to 

bottom system behavior. 

Credit: Michael 

Rubenstein, Harvard 

School of Engineering 

and Applied Sciences.

(Harvard, 2012) 

Computer scientists 

and engineers at 

Harvard University 

have created buglike ‘Kilobots’ that 

can interact and 

coordinate as a team, 

making it easier for 

researchers to test 

collective algorithms 

on hundreds or 

even thousands of 

tiny robots. In one 

demonstration 25 

Kilobots displayed 

team- or swarm-like 

behaviors such as 

foraging, formation 

control, and 

synchronization. The 

robots are modeled 

after insects like 

ants and bees 

that participate in 

coordinated group 

behaviors such 

as food foraging, 

transporting large 

objects, and nest 

building. Support 

for this work was 

provided by the 

National Science 

Foundation 

and the Wyss 

Institute.
20STRATEGIC OPPORTUNITIES

Build an inter-connected and interoperable shared 

development infrastructure —

Th e current market does not 

have governance or business models in place to motivate the 

development of networked, cooperating, human interactive 

systems. Developers must assume the risk of sharing proprietary 

information with competitors and the liability of successfully 

integrating their systems with external systems to ensure 

high levels of performance and functionality. Building an 

infrastructure foundation that is interoperable, contains a 

balance of open source and proprietary information, and 

operates under the same standards will provide a protected 

framework from which interoperability issues are minimized 

and system development could be profi table. For example, the 

manufacturers of autonomous cars will have to work with each 

other as well as with the developers of the traffi c regulating 

infrastructure to develop functional products. Building from 

a standard foundation would save time and cost through the 

sharing of critical information, while avoiding the liability of a 

solely proprietary product. 

Develop abstraction infrastructure to bridge digital and 

physical system components—Innovative approaches to 

abstractions3 and architectures that enable seamless integration 

of digital and physical systems for control, communication, and 

computation are needed for development of CPS. Th ese need 

to support and facilitate cost-eff ective integration. Recently, 

computers and networks have pushed ahead into monitoring 

and controlling a variety of physical processes including feedback 

loops. In these systems, issues arise from the safety and reliability 

requirements of the physical components that are qualitatively 

diff erent from those of the computing components. Because 

physical components are qualitatively diff erent from software 

components, standard abstractions that are only physical or only 

computational fail when used in CPS. 

For example, in communication networks, interfaces have 

been standardized between diff erent layers of the network 

stack to allow heterogeneous systems to operate in a plugand-play manner. Th is has created many opportunities for 

the proliferation of innovative technology and the Internet. 

However, today’s science and engineering knowledge base 

does not include similar standardized abstraction layers and 

architectures to support integration and interoperability in CPS 

(Lee, 2012). 3

 In computer science, abstraction is the process of fi nding an alternate 

representation that embodies less detail but maintains the properties of 

interest of the original representation. As such, an abstraction is always relative 

to a set of properties.
21STRATEGIC OPPORTUNITIES

Th e objective is to develop a 

collaborative, open, and highlyevolvable abstraction framework 

and infrastructure that spans 

multiple domains and applications. 

Th e outcomes would be a greater 

confi dence in the integration of cyber 

and physical components, the ability 

for system-wide and compositional 

evaluation, and greater openness of 

systems. 

WORKFORCE FOR 

CONTINUING 

INNOVATION

OPPORTUNITY

Dynamic, multi-disciplinary 

education and training

Building and sustaining a workforce 

capable of developing, innovating, 

and operating future CPS will require 

signifi cant enhancements in engineering 

curricula, renewed emphasis on systems 

sciences and engineering, and an 

increased emphasis on multidisciplinary 

research. Dynamic training programs 

for engineers, operators, and users of 

these systems will create pathways for 

keeping the workforce on top of new 

developments as they emerge. 

Establish multi-department CPS 

degrees and resources—University 

systems have historically been 

divided into traditional disciplines 

(e.g., computer science, electrical 

engineering). To build and sustain 

a future workforce for CPS will 

require the incorporation of multidisciplinary and targeted educational 

programs within the existing university 

structure. A prototype program could 

be developed in coordination with the 

National Academy of Engineering, the 

Accreditation Board for Engineering 

and Technology, and university 

organizations supporting research in 

CPS. Development of new textbooks 

and courses relevant to the curricula 

would need to occur in parallel. Th e 

objective is to create a more formal 

teaching and training approach in 

CPS leading to a new generation of 

scientists and engineers qualifi ed and 

interested in working in this fi eld. CPS 

educational programs will also appeal 

to students with an interest in new 

media by providing opportunities for 

gaining knowledge in emerging IT 

modalities.

Pursue dynamic training and 

certifi cation in CPS—CPS is a 

dynamic fi eld that requires continuous 

education and retraining. A number 

of approaches are possible, including 

development of CPS degrees, 

certifi cations, and accreditations, 

onsite training programs, or robust 

internships that allow for multidisciplinary training. For example, 

a joint industrial and academic 

certifi cation committee could be 

formed to develop a prototype test 

certifi cation and accreditation for CPS 

training. 

Credit: Midwest Center for

Structural Genomics

Twenty years ago, 

it took a week to 

purify a single protein. 

Today, robotic 

chromatography 

systems are 

making it possible 

to dramatically 

reduce the time 

needed for protein 

purifi cation. Above, 

Irina Dementieva, 

a biochemist, and 

Youngchang Kim, 

a biophysicist and 

crystallographer, work 

with the fi rst robot of 

its type in the U.S. to 

automate protein 

purifi cation. 
22STRATEGIC OPPORTUNITIES

CONCLUSION Th e potential of CPS to change every aspect of life is enormous. 

Concepts such as autonomous cars, robotic surgery, intelligent 

buildings, smart electric grid, smart manufacturing, and 

implanted medical devices are just some of the practical 

examples that have already emerged. Th ese systems all rely on 

a computational core that is tightly conjoined and coordinated 

with components in the physical world. 

As systems evolve they will shift the reliance on human 

decision making into new, more strategic aspects and will 

increasingly rely on operationalizing human knowledge through 

computational intelligence. Th is can yield many advantages, 

such as the computational core detecting and responding faster 

than humans, being more precise and less prone to fatigue than 

humanly possible, or expanding the capabilities of the system 

beyond the operator’s skills. As we become more dependent on 

CPS, the challenge is to design systems that are dependable and 

reliable—systems we can trust our lives with. Th is report is a call to action. Progress has been made, but there 

are many challenges ahead. Overcoming these challenges creates 

exciting opportunities to ensure that the U.S. is a technology 

leader in the fi eld of CPS with a globally competitive edge. 

Signifi cant challenges outlined in this call to action include: 

• Robust, eff ective design and construction of systems and 

infrastructure—key to designing dependable systems from 

the ground up and reducing cost and time to market;

• Improved performance and quality assurance—essential 

for spurring future investment, acceptance, and use of 

innovative systems that promise to provide revolutionary 

improvements to conventional practice; 
23CONCLUSION

• Eff ective and reliable 

system integration and 

interoperability—required for 

highly connected and networked 

components to work together 

eff ectively as a total system; and

• Dynamic, multi-disciplinary 

education and training—will 

make possible sustained growth 

and innovation and spawn a new 

generation of entrepreneurs, as 

well as the next generation of 

cyber-physical systems.

Credit: NIST, illustration by 

Michael Kemper

Artist’s rendition of 

superconducting 

quantum cable, 

which could enable 

future quantum 

computers to search 

databases and 

perform other tasks 

at exponentially 

higher speeds than 

today’s most powerful 

computers.
24REFERENCES

REFERENCES

GAO, 2010. Protecting the Federal Government’s Information Systems and 

the Nation’s Cyber Critical Infrastructures. Government Accountability 

Offi ce, 2010. Accessed 12/18/12. http://www.gao.gov/highrisk/risks/

safety-security/government_information_systems.php 

GE, 2012. Peter C. Evans and Marco Annunziata, Pushing the Boundaries 

of Minds and Machines. General Electric, November 2012. Accessed 

12/18/12. http://www.ge.com/docs/chapters/Industrial_Internet.pdf 

Harvard, 2012. “Kilobots are leaving the nest: Swarm of tiny, 

collaborative robots will be made available to researchers, educators, 

and enthusiasts.” November 21, 2011. Accessed 12/10/12. 

http://www.seas.harvard.edu/news-events/press-releases/kilobots-areleaving-the-nest and NSF News: http://www.nsf.gov/news/

news_summ.jsp?cntn_id=122415 

Lee, 2012. Edward A. Lee, Cyber Physical Systems: Design Challenges,

International Symposium on Object/Component/Service-Oriented 

Real-Time Distributed Computing (ISORC), May 6, 2008, 

Orlando, FL. 

MIT, 2012. “Robotic assistants may adapt to humans in the factory: 

New algorithm allows robots and humans to work side by side.” 

June 2012. MIT News Offi ce. Accessed 12/18/12. http://web.mit.edu/

newsoffi ce/2012/robot-manufacturing-0612.html

NREL, 2010. “NREL’s New Robots Scrutinize Solar Cells.” March 22, 

2010. National Renewable Energy Laboratory Newsroom. Accessed 

11/15/12. http://www.nrel.gov/news/features/feature_detail.cfm/

feature_id=1547

Nullmeyer et al, 2005. Nullmeyer, R.T., Stella, D., Montijo, G.A., 

& Harden, S.W., “Human factors in Air Force fl ight mishaps: 

Implications for change.” Proceedings of the 27th Annual Interservice/

Industry Training, Simulation, and Education Conference (paper no. 

2260), Arlington, VA, National Training Systems Association, 2005.

PCAST, 2012. Report to the President on Capturing Domestic Competitive 

Advantage in Advanced Manufacturing. President’s Council of Advisors 

on Science and Technology (PCAST), July 2012. Accessed 10/31/12. 

http://www.whitehouse.gov/sites/default/fi les/microsites/ostp/

pcast_amp_steering_committee_report_fi nal_july_27_2012.pdf

BAH, 2010. Systems-2020 Study, Final Report. Booz Allen Hamilton, 

2010. Accessed 12/18/12. http://www.acq.osd.mil/se/docs/

BAH-Systems-2020-Report-Final.pdf


ACKNOWLEDGMENTS

Advisors

National Institute of Standards and Technology

Clare Allocca

George Arnold 

Tanya Brewer

Howard Harary

Al Jones

Suzanne Lightman

Vijay Srinivasan

Mark Stolorow

Shyam Sunder

Albert J. Wavering

Report Preparation

Energetics Incorporated

For more information contact:

Albert J. Wavering

Chief, Intelligent Systems Division

Engineering Laboratory

National Institute of Standards and Technology

301-975-3418

wavering@nist.gov

www.nist.gov/el/isd 

Photos provided by:

iStockphoto (front and inside covers, pages iv, 1, 2, 3, 4, 6, 8, 9, 10, 

11, 12, 13, 14, 16, 20, 22, 24, inside back cover and back cover)

National Renewable Energy Laboratory (page 18)
FOR MORE INFORMATION CONTACT:

Albert J. Wavering

Chief, Intelligent Systems Division

Engineering Laboratory

National Institute of Standards and Technology

301-975-3418

wavering@nist.gov

www.nist.gov/el/isd