By Alain Louchez and Jay Sexton
Could the Internet of Things (IoT) be a victim of its success? Or perhaps more to the point, are IoT stakeholders beginning to realize that the deployment of IoT technologies is more complex than was first believed?
Gartner, famous for its hype cycles, had, early on, warned that before IoT reached stages where it is better understood (“slope of enlightenment”) and eventually widely adopted (“plateau of productivity”), it would have to go through a “peak of inflated expectations” and a “trough of disillusionment”.
We are now seeing throughout the IoT space a pause or a revisiting of the plans. There is no doubt that IoT is here to stay and expand, but expectations concerning timeframes, ease of deployment and rewards are being re-calibrated.
One of the reasons for the misunderstanding may lie in the nature of IoT. What is it? It is certainly not a single technology. Actually, we could argue that IoT per se does not even exist since there is not an Internet dedicated exclusively to things (regardless of their definition).
The expression is better understood as a metaphor describing the arrival of almost anything and everything into the communications space. Technologies enabling this arrival (so-called “IoT technologies”) are foundational elements of the broad digital transformation currently underway that will ultimately lead to a “pulsating world”, i.e., an environment where things constantly send and receive data. As endpoints are becoming smarter and smarter, IoT is about the interconnection of intelligent things. This transformation will radically revolutionize the way we live.
However, no successful revolution (or paradigm shift in science) can happen overnight. There is a long process of incubation and maturation; hence perhaps the chasm between performance and expectations.
Another source for misaligned IoT objectives is the number of variables that must be integrated into an IoT deployment. It is not just an engineering and a financial proposition, but rather a complex undertaking, which must seamlessly blend technological and human considerations.
A recently published White Paper from the IoT Thought Leadership Working Group of the Georgia Tech Center for the Development and Application of Internet of Things Technologies (CDAIT) on “Driving New Modes of IoT-Facilitated Citizen/User Engagement” explores these various dimensions and uses Smart Cities as a case in point to review several use cases.
Out of this, a screening model -- EPIC -- is proposed to determine what critical aspects must be addressed when contemplating an IoT deployment, especially for municipalities and any other organized collectivity in charge of public interest. . What follows is adapted from the White Paper.
EPIC IoT Implementation Model
EPIC integrates “hard” and “soft” -- qualitative and quantitative -- perspectives. In short, EPIC embraces a holistic approach to ensure that an IoT undertaking is successful. EPIC (see Figure 1) is about examining the project from four angles: Ethics, Profit (economic and social), Intimacy and Connectivity.
- Growing Attention. Ethical implementation of intelligent (including IoT-related) technologies is receiving a lot of focused attention worldwide as demonstrated by the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems, further underlining its paramount importance. Before (from the outset, by design) and during the implementation of any IoT device/service, ethical considerations must remain front and center to ensure that, as it changes, the system serves its purpose without undesirable impacts, be they on individuals, groups, the environment, the economy, or society as a whole.
- Ethical Values. In the EPIC model, ethical considerations are the set of “explicit or implicit values” that “prioritize the increase of well-being”, which must be satisfied for the successful deployment of IoT services.
- Ethics Focus. Defining these values is arguably hard to do, but buy-in from citizens will be more easily received if ethical focus is viewed as a top priority of the Smart City administration.
Profit (economic and social)
- Economic Profit. The notion of “economic profit” is straightforward. It is the positive financial return that all city stakeholders (private and public) receive from providing and/or using IoT devices/services. Since cities generally are non-profit entities whose financial objective is to minimize costs (under constraints such as fulfilling electoral promises), their economic benefit is the difference between costs before and after IoT; in other words, it boils down to productivity gains achieved with IoT technologies.
- Social Profit. On the other hand, “social profit” refers to the good done in, for and to the community (including protecting the environment and other elements related to the quality of life), and may or may not lead to an immediate monetary gain (see for instance David Grant’s “The Social Profit Handbook”). Although sometimes difficult to quantify, social profit is a critical objective.
- Profit Characteristics. Economic and social benefits can be tangible or intangible; direct or indirect (e.g., positive externalities); or quantitative or qualitative; but eventually they serve the whole community.
In this context, intimacy entails:
- Ease of access, i.e., is the IoT device/service user friendly, convenient?
- Mutual openness, i.e., do the IoT solutions facilitate the mutual and willing sharing of information between provider and user?
- Customized experience, i.e., does the service take into account the user’s particular conditions and needs (as opposed to a one-size-fits-all approach)?
Citizen/user intimacy is a key underpinning of a successful IoT deployment. If a lot of red tape wraps around the IoT-supported services (including legal and regulatory hurdles); if citizens feel that the city hides behind opacity and is shrouded in secrecy; and if technology does not bring about a personalized experience, it does not matter how great the system engineering is -- the deployment is bound to fail.
Connectivity is the overall technological foundation and includes:
- Medium, i.e., how is the connection between parties made? IoT devices are not all alike, and their need for connectivity varies widely; some (in great numbers) send a few bytes infrequently (“Massive IoT”), while others require always-on high-bandwidth connectivity with very low latency (“Critical IoT”).
- Computing, i.e., how and where is the transported data processed/analyzed? Where and to what degree the data captured by the physical interface (e.g., sensor) is going to be processed is a key and foundational element of any deployment of IoT technologies. Depending on several factors such as latency, availability, reliability and analytical needs, data processing should take place at the cloud, fog or edge levels (separately or in concert).
- Trustworthiness, i.e., how much can the whole connectivity system (the “technological conduit”) be trusted? Trust in the overall quality of connectivity (in the broad sense given here) requires several criteria to be satisfied. The National Institute of Standards and Technology (NIST) has singled out five key trustworthiness “concerns” as part of its Cyber Physical Systems Framework (Release 1.0) -- namely security, privacy, safety, reliability and resilience -- to aid IoT developers in identifying and resolving important issues for design, implementation and validation of IoT-based systems . Other concerns can certainly be added depending on system functionality and operational needs.
EPIC screen for the deployment of IoT technologies in cities
While there are conflicting views on the speed of IoT adoption, all agree that IoT is bound to become the catalyst of fundamental economic and societal (including military) changes. At the same time, it is becoming widely understood that successful implementation requires integrating various dimensions that are not always easy to apprehend. Paradoxically, engineering and overall technological aspects, while not trivial, may not be as complicated and challenging as human-centered issues. The proposed EPIC model ensures that both dimensions are fully and tightly woven into the analysis.
It follows that an IoT solution must not be seen as just the connection between a sensor/actuator and application software; it is part of a broader picture with economic and societal components. As a result, the recognition of the number and complexity of the moving parts in the IoT value chain has direct implications on the profile (education, training and experience) of the individuals engaged in IoT projects. They must have a variety of backgrounds, including social sciences and humanities, in addition to science and technology.
The National Institute of Standards and Technology (NIST) has singled out five key trustworthiness “concerns” as part of its Cyber Physical Systems Framework (Release 1.0) -- namely security, privacy, safety, reliability and resilience -- to aid IoT developers in identifying and resolving important issues for design, implementation and validation of IoT-based systems.
For a recent expansion and enrichment of the model created by the NIST CPS framework as applied to trustworthiness see Marcello Balduccini, Edward Griffor, Michael Huth, Claire Vishik, Martin Burns, and David Wollman, “Ontology-Based Reasoning about the Trustworthiness of Cyber-Physical Systems,” submitted on March 20, 2018 available here: arXiv:1803.07438v1
About the Authors
The views expressed in this article are solely the authors’ own and do not necessarily represent those of the Georgia Institute of Technology (“Georgia Tech”), the Georgia Tech CDAIT members, the University System of Georgia or the State of Georgia.
- Alain Louchez is the Managing Director of the Georgia Tech Center for the Development and Application of Internet of Things Technologies (CDAIT)
- Jay Sexton is the Chief Operating Officer of CDAIT