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ifip

International Federation for Information Processing

This document is the original author manuscript of a paper submitted to an IFIP
conference proceedings or other IFIP publication by Springer Nature. As such, there
may be some differences in the official published version of the paper. Such
differences, if any, are usually due to reformatting during preparation for publication or
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# Challenges in IoT Applications and Research

Luis M. Camarinha-Matos¹ and Srinivas Katkoori²

¹ School of Science and Technology and UNINOVA-CTS, NOVA University of Lisbon, Portugal
cam@uninova.pt

² CSE Department, University of South Florida, Tampa, FL, USA 33620
katkoori@usf.edu

**Abstract.** Internet-of-things (IoT) has great promise and immense potential in positively transforming the society for a better tomorrow. We can broadly approach the IoT system design from two perspectives, one from the basic research perspective and another from the applications perspective. Two panels have been organized on these topics to explore the relevant issues and challenges. The first panel entitled “IoT applications,” with three panelists and the second panel entitled “IoT research,” were organized as part of the IFIP IoT 2021 conference. Leading researchers participated in these panels sharing their research results, their views on the state-of-the-art, and promising future directions. In this article, we summarize the proceedings of the two panel discussions.

**Keywords:** Internet of Things, IoT engineering challenges, IoT research challenges, IoT trends.

## 1 Introduction

The area of Internet of Things has gone a long way since the term was first coined by Kevin Ashton in 1999. Along the last decades various efforts have been made to extend the concept, not only in terms of its supporting infrastructure and technology, but also in terms of its social, legal, and ethical implications [1], [2]. As the number of “things” connected to Internet has rapidly grown, organizational issues and the inter-relation with other systems, under a cyber-physical systems perspective, became part of the agenda.

As reflected in the contents of IoT 2021 and its previous editions [3], [4], the Internet of Things is characterized by a multidisciplinary nature, where various engineering and technology-oriented fields need to be combined with socio-organizational, legal, economic, and business-oriented contributions. In fact, it is rather impressive the number of technical contributions featuring fundamental research, technological developments, and advanced applications, that have been published in the last years. Yet, many of these publications tend to emphasize the perspective of a single discipline. The IFIP IoT series of conferences aim at creating an environment where an integrated multi-disciplinary and even interdisciplinary perspective can be nurtured.
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It is important to reflect on recent achievements and identify current challenges and emerging trends in both research and advanced applications towards solving complex societal problems. For this purpose, two panels were organized at IoT 2021 aimed at bringing together different perspectives and contributing to identify future directions:

- Panel 1, devoted to IoT Applications, involving contributions from Paulo Leitão, Adrian Florea, and Gerd Kortuem, and moderated by Luis Camarinha-Matos.

- Panel 2, devoted to IoT Research, including contributions from Elisa Bertino, Marilia Curado, Carlo Fischione, and Paul Havinga, and moderated by Srinivas Katkoori.

This article briefly summarizes the main issues discussed in these panels, highlighting the main conclusions.

# 2 Challenges in IoT Applications

## 2.1 Scope

The scope of IoT applications has been progressively expanding to address more complex systems. More and more researchers are asked by funding agencies to position their work in the context of the United Nations goals for sustainable development (Agenda 2030) [5]. As society and its supporting systems are becoming hyper-connected, IoT needs to be considered in a more integrated and holistic perspective, which also demands adequate engineering methodologies. In order to guide the discussion of these challenges, the invited panelists were asked to organize their contributions according to three guiding questions:

- What are the main engineering challenges in IoT development?

- What are the critical success factors in advanced IoT applications?

- Which futuristic application scenarios do you envision for the next 5-10 years?

The following sections highlight the main ideas resulting from the panelists' statements and also from the discussion with the conference attendants.

## 2.2 Main Engineering Challenges in IoT Development

Despite the technological advances of last decades, there are still critical technological challenges requiring further developments. This includes:

- Security, privacy, and data protection mechanisms.

- Further developments in power supply for IoT devices (batteries and energy harvesting), low energy protocols and computing.

- More focus on "actuation" and not only on "sensing".

- Integration of AI and machine learning.

- Development and integration of bio devices.

- Development of very low cost IoT devices (for mass applications).

- Increased maturity of standards. Current multiplicity of standards is often an
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Complementarily, it is necessary to invest more on methodological approaches to deal with:

- Complex IoT-based systems design.

- Integration of heterogeneous and evolving systems.

- Interoperability, legacy systems, and ubiquitous connectivity.

On the modeling side, further efforts are needed on:

- Organizational models for complex IoT/CPS systems including a large number of devices and subsystems.

- Collaboration models for autonomous, semi-autonomous, and evolving systems of smart systems.

- Distributed cognition models.

Besides the applications in traditional domains, e.g., manufacturing / industry, healthcare, smart cities, it is necessary to facilitate the penetration of IoT in other domains not so widely addressed yet, e.g., agriculture, and wildfires management, which requires an understanding of the specific "culture" of those domains and the involved value creation processes.

IoT development also poses questions of a socio-technical nature, including:

- Education and upskilling of engineers with a multi-disciplinary culture.

- Coping with different cultures and terminology in different application domains.

- Understand and comply with ethical principles and data protection regulations.

As an overarching context, there is a need for a strong emphasis on sustainability:

- Towards sustainable IoT, including reducing electronic waste.

- Maximizing trust, through transparent and scrutable algorithms, including explainable AI.

- Maximizing protection towards verifiable secure IoT.

## 2.3 Critical Success Factors in Advanced IoT Applications

A crucial success factor is to develop an "IoT that we can control", an "IoT that we can context", and "IoT that we can rely on". Certainly, we cannot ignore IoT, which has become a kind of "societal infrastructure", but not always beneficial. As such, a democratic society should be able to decide on which levels of transparency and which kind of values it prioritizes.

This factor relates again to the issue of trust and scrutable systems and raised the question of "ethics embedded in systems". On this issue there was no consensus among participants, with opinions going from "yes, we should implement ethics in systems" to "no, we should not". Main arguments from the "no side" question the origin of the ethics principles, which are never perfect, not fixed, and evolving. As an alternative, it was pointed out that we need to be able to audit systems. Thus, we need to design systems to be auditable. Another opinion pointed out that more than auditable, we need verifiable systems.

Further discussed factors include:
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## 2.4 Futuristic Application Scenarios for the Next 5-10 Years

A vast array of application scenarios was discussed, including improvements of current types of applications and disruptive directions. Examples:

- Combination of augmented reality and IoT for improved services and entertainment.

- Advanced smart city infrastructures, including smart mobility.

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- Improved customer services and customer experience.

- Improved health monitoring and diagnosis with edible nano devices and wearable IoT.

- Intelligent industrial environments facilitating sustainability, resilience, and human-centric perspectives (towards Industry 5.0).

- Support of digital transformation.

- Use of nano devices in agri-food monitoring, traceability, and quality control.

- Precision farming and smart agriculture, resorting to IoT sensors and actuators. Examples: environment and crops monitoring, smart irrigation and fertilization, predictive analytics, plant disease detection and pest control, livestock tracking and geofencing, smart greenhouses, etc.

- Expanded IoT usage in climate monitoring and climate change prediction.

- Real-time monitoring of constructions (buildings, roads, infrastructures).

All these developments shall be driven by general sustainability concerns, and designed for transparency, accountability, and verifiability.

## 2.5 Concluding Remarks

As a final outcome of this panel, there is a general message of optimism regarding the high potential of IoT in helping to address major societal challenges and plenty of directions for a future applied research agenda. Nevertheless, all developments need to be human-centric, verifiable / scrutable, and responsible.

# 3 Challenges in IoT Research

## 3.1 Scope
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IoT represents an ongoing technology transition bringing together many component technologies pertaining to diverse research domains such as internet, wireless communication, cloud computing, big data, data analytics, cybersecurity, etc. It is critical to identify immediate research challenges that needs to be met. While individually, impressive strides are being made in each of the constituent component technologies, what is critical and needed is a systems level thinking cross-cutting diverse research topics. Fortunately, this is happening in the form of many international research conferences focused on IoT (such as this conference) as well as dedicated tracks in established research conferences on the component technologies.

To guide the discussion of these challenges, the invited panelists in the second panel were asked to organize their contributions according to three guiding questions:

- What are the current IoT research challenges?

- What are the promising approaches to face such challenges?

- What emerging technologies are likely to have an impact in next 5-10 years?

The following sections highlight the main ideas resulting from the panelists' statements and from the discussion with the conference attendants.

## 3.2 Main Current IoT Research Challenges

Any practical IoT system is very complex due the scale (scalability) and diverse (heterogeneous) interacting component technologies (interoperability) [6]. The sheer complexity is overwhelming and gives rise to many research challenges. The IoT design problem is complicated as many of the challenges must be addressed simultaneously. The panel thinks that many research challenges are domain dependent (e.g., smart farming, healthcare IoT, industrial IoT, etc.). Further, the research complexity is captured well in the statement, "*IoT research is a system of systems research.*"

The following are the main research challenges that the panel has identified as quintessential to be addressed with high-quality research:

- *Security and Trust* – The success of an IoT system depends on how secure it is. Naturally its wide-scale adaptability requires that it is trustable. Unfortunately, security and trust cannot be easily guaranteed. The definitions of security and trust itself changes depending on the IoT system at hand. Thus, domain dependent security challenges need to be understood well.

- *ML and IoT* – Many aspects of IoT are increasingly dependent on AI/ML which requires a lot of careful and high-quality research. IoT system automation can be accomplished with artificial intelligence. The system complexity necessitates that it learns by itself over time which perhaps is initially trained through supervised learning approach. ML model development from collection of training data to chosen model (network characteristics) to validation involves humans. It is critical that unintentional biases should not seep into the model. Good processes must be developed that will help in collected "good" training data.

- *Data privacy* – IoT systems generate lots of data which can be sensitive (e.g., healthcare monitoring data) and must be protected. Ensuring data sovereignty
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must be researched wherein data ownership must be identified with data sharing rights assigned to the rightful owner. Privacy can have different definitions depending on the contexts. Privacy-by-design research is required wherein end users can easily opt-out and want to remain anonymous by choice. Currently, no such option exists. One possibility is to keep the data where it is generated and only share the insights from the data. If the data have to be transported, then automated network anonymizers need to be researched.

- *Energy efficiency* – One of the main bottlenecks is energy efficiency. The edge devices need to be constantly powered and their power must be managed to optimize the power consumption. While devices are cheap, powering them efficiently is a critical problem.

- *Connectivity and communication* – For IoT reliable and secure connectivity is very important. Cellular technologies such as 5G and upcoming 6G are critical to the success of IoT. Ubiquitous energy efficient connectivity must be researched. Bandwidth limitations is a well-known bottleneck to the success of IoT, research is needed to increase bandwidth. One challenge in wireless IoT is the difficulty in incorporating ML training and inference in real-time. Security in existing and evolving communication technologies needs further research attention.

- *Legacy systems* – It is important that legacy systems with old protocols must be brought in that requires convergence of old operational technology with information technology. Research is needed into how this transition can happen in a reliable and efficient manner.

- *Regulation and Certification* – While the regulation is not a complete answer to guarantee a safe and secure system, it has an important role to play in IoT system certification. Regulation may be difficult to enforce, however, there is a need for regulation that can bring awareness in the end users as well as the administrators of an IoT system. To the extent possible, component technologies should be certified.

## 3.3 Promising Approaches to Face the Challenges

The panel has suggested many promising directions to face the research challenges identified above. They are:

- *Safety and security research* - A systematic approach to security need to be adopted that in general will have four progressive stages: (1) prepare and prevent; (2) monitor and detect; (3) diagnose and understand; and (4) react, recover, and fix. Safety issues can be addressed by an approach for constrained reinforcement learning (well established technology). Systematic identification of vulnerabilities in existing technologies (such as 4G and 5G).

- *IoT standardization* – Standardization will result in methodical design (vs. adhoc design) that will help handle the IoT design complexity better. Legacy systems can interface better with standard modern technologies.

- *Design approaches* – As IoT system has foundation in diverse component technologies, a multi-disciplinary approach is needed. Such an approach will break silos and will lead to more robust systems. Open system design approach
is highly promising as this will lead to contributions from research community with crowdsourcing similar to what the software design world has seen. When an IoT system fails, there is a need for forensic analysis as to what happened and the order of events. Thus, forensic analysis tools for IoT need to be researched.

- ML and IoT - ML for wireless IoT can be achieved by: (a) data-driven optimization of network operations; (b) data-driven redesign of PHY or Link Level protocols; (3) redesign or adaptation of wireless access protocols to support ML services. Distributed ML over wireless IoT (Edge AI) is a promising direction due to resource constraints (processing, storage, and power). One aspect of IoT system is that humans interact in many ways (sometimes erroneously!) which necessitates smarter and adaptive algorithms.

- Edge and Cloud Computing - Ongoing research in edge computing is in the right direction particularly with embedded AI that can lead to smarter IoT systems with optimized resource orchestration. Battery free operation of edge devices is critical as current battery technology cannot meet the long-term needs of IoT without replacement/maintenance. Cloud computing research into big data, distributed computing, platform-as-service, etc., are important ongoing research that will greatly contribute to IoT success. Secure data spaces will enable secure multi-party computation and federated learning. The panel believed that federated learning is an important emerging technology with significant impact on IoT.

## 3.4 Emerging Technologies that are Likely to Have an Impact in the Next 5-10 Years

The panel identified many promising technologies many of which are already in advanced implementation stages, while some are very futuristic in nature:

- 5G, 6G, Mesh technologies.

- Standardization, Open system design approach, Event-driven IoT, Digital twins, Human IoT interfaces.

- IoT cyber threat intelligence, Root-of-trust HW approaches, Embedded AI enabling real-time interaction, privacy, and efficiency.

- Tiny ML, Federated AI.

- Data driven applications and society.

- Augmented and extended reality (metaverse), The Internet of senses (>5 years), Real-time music interaction over internet.

- Autonomous driving, Personal health monitoring, Smart Cities, Drones, Bio-nano things (IoBNT).

- Combined sensing and communication (optical and satellite communication).

- Quantum technologies (sensing, communication, computing).

## 3.5 Concluding Remarks

In conclusion, the panel agreed that IoT research is an exciting topic with interesting
challenges. They encouraged young or starting researchers to consider IoT as their research field. The panel felt that there are many opportunities in the IoT field. If the research challenges are addressed successfully then it will solve many societal problems and positively contribute to the progress of humankind. IoT can make the world better and healthy (e.g., can we predict a pandemic?). For this we require a very careful approach to research both basic as well as applied research.

## 4 Conclusions

Both panels agree that IoT will be a major contributor to addressing big societal challenges such as global healthcare, global food system, wildfire management, sustainability, etc. There is a need for a multi-disciplinary perspective; technology-only approaches will fall short, they need to be judiciously combined with socio-technical research, ethics research, regulation and certification standards, appropriate education, and global awareness. IoT research and development shall be driven by general sustainability concerns, and designed for transparency, accountability, and verifiability. Future IoT applications include, for instance, Internet-of-senses, Internet-of-BioNanoThings, augmented and extended reality, improved health monitoring and diagnosis with edible nano devices.

**Acknowledgments.** We would like to thank the seven panelists and the conference audience for two thought-provoking and exciting panel discussions.

## References

1. Sundmaeker, H., Guillemin, P., Friess, P., Woelfflé, S. (eds.) (2010): Vision and Challenges for Realising the Internet of Things. CERP-IoT, European Commission.

2. Camarinha-Matos L.M., Goes J., Gomes L., Martins J. (2013) Contributing to the Internet of Things. In: Technological Innovation for the Internet of Things. DoCEIS 2013. IFIP AICT, vol 394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37291-9_1

3. Strous, L., Cerf, V. G. (eds) (2018): Internet of Things - Information Processing in an Increasingly Connected World. Proceedings IFIP IoT 2018, IFIP AICT 548, Springer Cham. https://doi.org/10.1007/978-3-030-15651-0

4. Casaca, A., Katkoori, S., Ray, S., Strous, L. (eds) (2020): Internet of Things. A Confluence of Many Disciplines. Proceedings IFIP IoT 2020, IFIP AICT 574, Springer Cham. https://doi.org/10.1007/978-3-030-43605-6

5. United Nations (2015): Transforming our world: the 2030 Agenda for Sustainable Development. https://sdgs.un.org/2030agenda (accessed 30 Nov 2021).

6. Hanes, D., Salgueiro, G., Grossetete, P., Barton, R., and Henry, J. (2017) IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet-of-Things. Cisco Press.