Article 1

The Global Observatory for Urban Intelligence: Unraveling the Complexities of City Ecosystems

Joel Myers, Gyu Myoung Lee, Victor Larios, Mohamed Essaaidi, and Adam Drobot

Today, the goal of creating sustainable resilient cities is still, for the vast majority, an unrealized dream and very much an uphill struggle. However, COVID-19 has brought with it a stark wake-up call. A shared global realization that the very “local” places we live in, where we work, and visit, are, in fact, extremely fragile. They will not survive, nor will we, the majority of the world’s population that call a city their “home”, without a firm grounding in a truly sustainable and resilient framework.

 


Article 2

Time-critical IoT Communication with 5G NR: A Technical Overview

Torsten Dudda

5G New Radio (NR) is equipped to fulfill time-critical communication needs, resulting in several emerging use cases in the areas of real-time media, mobility automation, and remote control, as well as, industrial automation IoT. 5G is known to serve a wide range of use-cases and devices that go well beyond smartphones and mobile broadband.

 


Article 3The Internet of … What ??!

Nahum Gershon

Suzanne Simard discovered that “fungal threads link nearly every tree in a forest — even trees of different species. Carbon, water, nutrients, alarm signals and hormones can pass from tree to tree through these subterranean circuits."

 


Article 4Our Stealthy Housemates: Consumer IoT Devices, Privacy Risks, and Potential Mitigations

Anna Maria Mandalari, Hamed Haddadi, Daniel J. Dubois, and David Choffnes

Consumer Internet of Things (IoT) devices are gaining an increasing presence in our homes, with the promise to deliver unprecedented benefits and personalized services. The increasing range of sensors embedded in these devices, alongside the availability of sophisticated AI models and interactions mechanisms (e.g., voice-based smarthome assistants), present a complex range of functionalities, analytics, and capabilities. However, this complexity results in our inability to fully assess and establish the reliability and trustworthiness of these devices, in addition to their security threats and privacy risks, despite our increasing dependence on these devices and their underlying services.

 

 

EVENTS & ANNOUNCEMENTS


Article 5

IEEE Internet of Things Initiative - Upcoming Events

IEEE 7th World Forum on Internet of Things - 2021
14 June-31 July 2021 // New Orleans, Louisiana, USA / Hybrid Event
Register today for the upcoming WF-IoT 2021
Tutorial Week - 14-18 June
Core Conference -- Live from New Orleans! - 21-23 June
Women In Engineering Program - 25 June
Workshops/Special Sessions and Technical Paper Discussions - 18 June-1 July
Vertical and Topical Tracks - 12-23 July
Entrepreneurial Program - 26-30 July

IEEE IoT Vertical and Topical Summit on Tourism
20-24 September 2021 // Virtual Event
Submit a paper today!

IEEE International Conference on Omni-layer Intelligent Systems 2021 (IEEE COINS 2021)
23-25 August 2021 // Barcelona, Spain

IEEE COINS includes a multi-disciplinary program from technical research papers, to panels, workshops, and tutorials on the latest technology developments and innovations. IEEE COINS will address all important aspects of the IoT ecosystem from smart things to the circuit and system, design automation, Edge-Fog-Cloud computing, big data, machine learning, artificial intelligence, blockchain, security, and smart products/services as well as business models. IEEE COINS solicits papers and proposals accompanying submissions for presentations in the Vertical and Topical Tracks. Please visit the website for more information.


Article 5

IEEE Internet of Things Magazine

Internet of Things Magazine logoThe IEEE Internet of Things Magazine solicits high quality articles that: a) describe in depth and/or breadth the state-of-the-art multi-disciplinary IoT-centric research and deployments, b) present groundbreaking novel practical contributions and insights into emerging IoT hot topics and futuristic applications, c) develop/share best practices, vision and lessons learned on integrated IoT environments, and d) establish guiding principles for the advancement of IoT-centered research as well as for the technical, operational and business successes.

Become an author - Submit an article today!
Never miss a copy - Subscribe today! 

This Month's Contributors

Joel Myers is a leading international technologist, specialising in the creation and development of innovation technology solutions in Cultural Heritage, Tourism, and Smart Cities, working internationally with state and local government, and industry.
Read More >>

Gyu Myoung Lee is with the Liverpool John Moores University (LJMU), UK and with KAIST Institute for IT convergence, Korea.
Read More >>

Victor M. Larios is a Professor at the Information Systems Department at the University of Guadalajara in Mexico.
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Mohamed Essaaidi is Head of the Smart Systems Lab and Former Dean, ENSIAS College of Engineering, Mohamed V University in Rabat.
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Adam Drobot is an experienced technologist. His activities are strategic consulting, start-ups, and industry associations.
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Torsten Dudda is a Master Researcher at Ericsson located in Aachen, Germany.
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Nahum Gershon focuses on social media, the Internet of Things, strategic planning, visualization, combining creative expressions with technology and real-time information delivery, presentation & interaction (including storytelling) in mobile, wearable as well as traditional devices including how they could improve both organizational environments and our personal lives.
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Anna Maria Mandalari is a Research Associate in the Dyson School of Design Engineering at the Faculty of Engineering at Imperial College London.
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Hamed Haddadi is an Associate Professor at Imperial College.
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Daniel J. Dubois is an Associate Research Scientist at Northeastern University, his research is rooted in software engineering, with a current focus on IoT privacy.
Read More >>

David Choffnes is an Associate Professor at Northeastern University, member of the Cybersecurity and Privacy Institute, and affiliate faculty at the Center for Law, Innovation and Creativity (CLIC).
Read More >>

 

Contributions Welcomed
Click Here for Author's Guidelines >>

 

Would you like more information? Have any questions? Please contact:

Raffaele Giaffreda, Editor-in-Chief
rgiaffreda@fbk.eu

Massimo Vecchio, Managing Editor
massimo.vecchio@uniecampus.it

 

About the IoT eNewsletter

The IEEE Internet of Things (IoT) eNewsletter is a bi-monthly online publication that features practical and timely technical information and forward-looking commentary on IoT developments and deployments around the world. Designed to bring clarity to global IoT-related activities and developments and foster greater understanding and collaboration between diverse stakeholders, the IEEE IoT eNewsletter provides a broad view by bringing together diverse experts, thought leaders, and decision-makers to exchange information and discuss IoT-related issues.

The Global Observatory for Urban Intelligence: Unraveling the Complexities of City Ecosystems

Joel Myers, Gyu Myoung Lee, Victor Larios, Mohamed Essaaidi, and Adam Drobot
May 18, 2021

 

Today, the goal of creating sustainable resilient cities is still, for the vast majority, an unrealized dream and very much an uphill struggle. However, COVID-19 has brought with it a stark wake-up call. A shared global realization that the very “local” places we live in, where we work, and visit, are, in fact, extremely fragile. They will not survive, nor will we, the majority of the world’s population that call a city their “home”, without a firm grounding in a truly sustainable and resilient framework.

The lessons we can learn from this tragic pandemic must include how best to nurture our cities, develop the policies, strategies, and solutions needed to safeguard our social well-being, and protect us against what the future may hold in store.

Whatever terms or definition we use for “Smart Cities”, we know that technology and access to intelligent data are at the core of providing sustainable and resilient cities. Not simply for providing efficiencies for a city’s limited resources, but in stimulating local economies, providing social well-being to citizens, and defining the type of city we want for future generations.

The quantity of data being created globally is astronomical. Hundreds of exabytes of data are generated every year. Every 2 days we produce more data than all of history before 2003 [1]. This surge in data generation is led by the omnipresence of ICTs and digital technologies in our everyday practices and environment. The drive for smart cities has resulted in the dawn of a wealth of urban data, where communication technologies such as low power consumption for IoT devices like sensors, in combination with standards protocols permitting meshes connected in metropolitan networks, allow cities to scale and grow data acquisition [2].

Yet, today, even after a few decades of digital in our cities, in our daily lives, and this data deluge, the understanding we have of the highly complex behaviors that are intrinsic to cities and us, its people and best asset, remains, very much, a mystery. We are in the early stages of urban data production. By 2025 we are expected to reach close to 35 billion IoT devices in cities, producing 79.4 Zettabytes of unstructured information [3]. There is a critical need to resolve the limits of having mainly silos-based urban data; security and privacy issues; and the trustworthiness of their source, through a unified vision that data fusion can help provide [4].

It is certainly true, that we have an ever-growing knowledge base of observable urban phenomena when it comes to “silos-based” data. However, cities are composed of people, infrastructure, and resources, which do not function in singular myopic worlds. Quite the opposite. They live, breathe, and nourish continuously intertwining and extraordinarily complicated relationships. Currently, to take advantage of the silos-based data coming for decision-making, city authorities are constantly having to redevise their urban governance to address the complexity of socio-technical systems [5].

To best understand a city, we must discern its political systems and governance mechanisms, its social and cultural makeup, diversity and behavior, as well as its financial framework and economies. They each affect changes in the city, continuously, in every single moment in time. It is a highly fluid and profoundly intricate system.

If we are to achieve sustainable and resilient cities, then delivering a new model of understanding their complexity is a key next step we must take.

From an international outlook, cities do not function in isolated vacuums. Sharing of knowledge and experience in building this sustainability across the globe means accepting the very heterogeneous nature that is the essence of the world we live in. Diversity in language, spoken as well as sectorial. Diversity in our cultures, social systems, political and economic structures, our environments, and resources, which in itself creates an area of opportunity in standards, where the technology and framework process for planning a Smart City can be improved by considering this heterogeneous nature of cities instead of isolated use cases.

To share knowledge on cities, collaborate, and develop ad-hoc sustainable models across global regions, we need to develop a common language. Not in terms of single-spoken, or written languages, but instead, as a common ontology of terms that best represents the multi-aspects and disciplines of smart cities. Whether we need to understand recycling of waste, transport, education, or the environment (to name a few), we need to tackle the technical language of each aspect as described by its engineering, urban planning, technology, cultural and environmental impact, governance, economies and so on. We also need to ensure that the ontology communicates across international languages, cultures, political systems, and economies.

This common language or smart city ontology must also embrace the subjective perspectives of our cities and our lives. Otherwise, it remains just informative data, without representing the true nature of a city or its people. Besides, in the era of digital twins, without ontologies, it is not possible to create adaptive models of digital twins that evolve in sync with cities [6].

This year, under the Smart Cities WG and Global Cities Alliance program of the IEEE IoT Initiative, IEEE has launched an informal collaboration with ITU to develop the “Global Observatory for Urban Intelligence” to unravel some of the complexities within urban ecosystems by providing an ongoing understanding of cities and how digital transformation can best serve cities in developing social, economic, and environmental dimension of urban growth, for sustainability and resilience, through:​

  • Smart Cities Ontology: develop or use an existing common language to communicate smart cities across cities, nations, global regions, based on a multi-disciplinary approach; ​
  • Correlations: build or use existing relationships between the ontology’s objects to best represent the complex behavior of a city’s ecosystem, based on a multi-disciplinary approach and using AI/ML to automate much of this process​;
  • Develop an international community of city observatories, as a collaboration between local authorities and academia that will gather and upload data on an ongoing basis to the GOUI’s cloud-database​;
  • Develop or adapt existing open-source tools for querying, modeling, and using AI/ML for understanding, sharing, and comparing smart cities, for policy-making, strategic decision-making, piloting and monitoring, as well as prediction and risk analysis​;
  • Create and provide a playbook and best practices on how to work with the above resources of the “Global Observatory for Urban Intelligence”, whichever level of technical expertise the user may have. Publish various deliverables including reports, catalogs, and any other outputs that can be produced in the future with the ontology/data.  Determine governance mechanisms for the validation of all these items​;
  • Provide users with the communications tools to network, share and collaborate, based on the resources of the “Global Observatory for Urban Intelligence”​.

The “Global Observatory for Urban Intelligence” will be developed on an open-source cloud platform using crowd-sourcing collaborative tools, where components will be developed in multiple phases, from its Smart City Ontology to Correlation, then Data gathering, Modelling, and AI/ML. For each phase, open-source tools will be used where possible to automate processes, and step-by-step results will be tried and tested across global focus groups.​

This initiative is crowd-sourced and we welcome contributions and participation from a government, industry, young professionals, research, smart city networks, civic associations, international agencies, NGOs, and academia (professors and students) on a global scale, especially through the international and regional outreach of IEEE and ITU membership.

If you are interested in getting involved, please contact Joel Myers, the Co-Chair of the Smart Cities WG of the IEEE IoT Initiative at joel.myers1@gmail.com.

References

  1. R. Smolan and J. Erwitt, “The Human Face of Big Data,” Against All Odds Productions, 2012
  2. A. Kochhar and N. Kumar, “Wireless sensor networks for greenhouses: An end-to-end review,” Comput Electron Agr, vol. 163, p. 104877, 2019.
  3. S. Iyengar, V. K. Gurbani, Y. Zhou, and S. Sharma, “Opportunistic Prefetching of Cellular Internet of Things (cIoT) Device Context,” 2018 27th Int Conf Comput Commun Networks Icccn, pp. 1–6, 2018.
  4. G. K. Canalle, A. C. Salgado, and B. F. Loscio, “A survey on data fusion: what for? in what form? what is next?,” J Intell Inf Syst, pp. 1–26, 2020.
  5. M. Razaghi and M. Finger, “Smart Governance for Smart Cities,” Proceedings of the Ieee, vol. 106, no. 4, pp. 680–689, Apr. 2018.
  6. J. A. Erkoyuncu, I. F. del Amo, D. Ariansyah, D. Bulka, R. Vrabič, and R. Roy, “A design framework for adaptive digital twins,” Cirp Ann, vol. 69, no. 1, pp. 145–148, 2020.

 

joel myersJoel Myers is a leading international technologist, specialising in the creation and development of innovation technology solutions in Cultural Heritage, Tourism, and Smart Cities, working internationally with state and local government, and industry. His company, HoozAround Corp. (USA) owns and manages a digital platform called IoP (the “Internet of People”) that provides socio-economic recovery for cities, through a micro-currency called HooziesTM.  As Chair of IEEE IoT Initiative for Smart Cities, Joel Myers has been focusing his working group on the redefinition of the digital transformation of urban environments from a truly "People-Centric" focal point. The work carried out by Joel Myers has been published in international newspapers and journals such as the BBC, New York Times, Hong Times, the Hindu Times, Wired, and Forbes Magazine.

 

Gyu Myoung LeeGyu Myoung Lee is with the Liverpool John Moores University (LJMU), UK and with KAIST Institute for IT convergence, Korea. Before joining the LJMU, he worked with the Institut Mines-Telecom, Telecom SudParis, France, from 2008. He has been actively working for standardization in ITU-T, IETF and oneM2M, etc., and currently serves as a WP chair in SG13, the Rapporteur of Q16/13 and Q4/20 as well as a vice-chair of ITU-T Focus Group on Autonomous Networks. He was also the chair of ITU-T Focus Group on data processing and management (FG-DPM) to support IoT and smart cities & communities. He is a Senior Member of IEEE.

 

Victor M LariosVictor M. Larios is a Professor at the Information Systems Department at the University of Guadalajara in Mexico. In April 2014, Dr. Victor M. Larios founded and became director of the “Smart Cities Innovation Center (SCIC)” at the University of Guadalajara, where he leads a group of researchers in Smart Cities and Information Technologies. The SCIC is a think-thank to help government, industry, and other academic partners to join efforts to improve the quality of life and social well-being within an urban environment, by using technology as the core driver for transformation. Since 2013, he has led the “Guadalajara Core City” in the IEEE Smart Cities Initiative.

 

Mohamed EssaaidiMohamed Essaaidi is Head of the Smart Systems Lab and Former Dean, ENSIAS College of Engineering, Mohamed V University in Rabat. He is also the founder and former Chair of the IEEE Morocco Section. His biography was listed in Who’s Who in The World in 1999. He is also the co-founder and the current coordinator of the Arab Science and Technology Foundation (ASTF) RD&I network on Electrotechnology, as well as and General Chair of the Mediterranean Microwave Symposium (MMS). His research interests focus mainly on RF and microwave passive and active circuits and antennas for wireless communications and medical systems

 

Adam DrobotAdam Drobot is an experienced technologist. His activities are strategic consulting, start-ups, and industry associations. He is the Chairman of the Board of OpenTechWorks, Inc. In the past, he was the Managing Director and CTO of 2M Companies, the President of the Applied Research at Telcordia Technologies (Bellcore) and the company’s CTO. Previous to that, he managed the Advanced Technology Group at Science Applications International (SAIC/Leidos) and was the Senior Vice President for Science and Technology at SAIC. Adam is a member of the FCC Technological Advisory. He has published over 150 journal articles and holds 27 patents.

 

 

Time-critical IoT Communication with 5G NR: A Technical Overview

Torsten Dudda
May 18, 2021

 

5G New Radio (NR) is equipped to fulfill time-critical communication needs, resulting in several emerging use cases in the areas of real-time media, mobility automation, and remote control, as well as, industrial automation IoT. 5G is known to serve a wide range of use-cases and devices that go well beyond smartphones and mobile broadband.

New real-time applications are enabled that require guarantees of low latency with high reliability, i.e., ultra-reliable low latency communication (URLLC) [1]. In addition, 5G provides the functions and interfaces to become integrated with advanced industrial communication standards, such as IEEE Time Sensitive Networking (TSN). In the following, we explain the features introduced to the 5G NR standard that keep its latency within guaranteed bounds, hence enabling Industrial IoT use cases.

Time-critical IoT Communication Use-cases and Requirements

Many industries can benefit from integrating devices with time-critical requirements wirelessly into their IoT systems. Several examples can be envisaged [2], as shown in Figure 1:

Figure 1: Time-critical communication use-cases [2].

Figure 1: Time-critical communication use-cases [2].

  • Mobile AR devices with off-loaded rendering and processing from the Augmented Reality (AR) device itself to the edge cloud. A 5G connection with bounded latency makes this possible.
  • Similarly, real-time media or online gaming devices wirelessly connected via 5G can be enhanced with additional information and processing in the edge cloud and provide richer interactivity with other users.
  • Vehicles and machines can be remote-controlled, based on video or AR overlay, with a robust wireless connection. The vehicles may even be integrated into a mobility automation system controlled by the edge cloud itself.
  • In smart manufacturing environments, simplicity and flexibility for any reconfiguration of the factory are dramatically increased by replacing cables with dependable wireless connections. Sensors and machines, like robots, may then be operated by a centralized controller.

These use cases all depend on a fast, dynamic response to changes in the environment, and therefore rely on the interaction between the wirelessly connected entities with short round-trip times, which for the use cases above, lie in the tens of millisecond to the one-millisecond range. It’s important to reach these latencies with a very high probability (reliability) for the systems to operate properly. These reliabilities, expressed in success rates of packets reaching the receiver within a latency bound, are in the order of 99 to 99.999 percent.  

Bounded-latency Scheduling with 5G NR

In wireless communication, the reliability bottleneck was traditionally the radio interface due to limited available transmission bandwidth, the signal-to-noise ratio at the receiver, and the time to transmit. This is, in particular, the case for the real-time use-cases requiring a strict latency bound. In cellular systems, spectrum resources are scarce and are shared among all connected devices in the cell. Hence, to improve reliability, the cellular system has the optimization target to organize itself so that the right amount of spectrum is used by the right device at the right time. Quality of service (QoS) and bounded low latency are achieved by centralized admission control and scheduling of the wireless frequency resources, which are typically licensed frequency bands assigned to a network operator. The scheduler can choose from a variety of features to achieve QoS in terms of latency and reliability for the user.

For a certain segment of the spectrum, the NR base station (gNB) scheduler can choose the spectral characteristics of a signal, which also includes the duration of a schedulable transmission slot, i.e., the time granularity. For a typical NR mid-band spectrum around 3.5 GHz, the slot duration is 0.5 ms; and for mmWave spectrum, it is even shorter, 0.125ms. Furthermore, processing times also need to be accounted for. In NR, the encoding and decoding of the transmissions can be as fast as a fraction of the actual slot duration. Another latency component is the alignment delay, i.e., the time from when data is provided to the 5G network until the next transmission slot starts. The NR standard also allows sub-dividing a slot further into sub-slots. With seven sub-slots, the duration would be shortened from 0.5ms to ~0.071ms for mid-band, or from 0.125 ms to ~0.02 ms for mmWave [3]. Latency-critical application data would, when using these techniques, wait for less until the next transmission opportunity and, as a result, the data is transmitted faster over the air. In addition, the round-trip time until retransmission occurs scales down – if it’s the case that the initial transmission did not succeed.

For extra robust transmissions, NR specifies modes for increased reliability, for both data and control radio channels. Reliability is further improved by various techniques, such as multi-antenna transmission, the use of multiple carriers, and packet duplication over independent radio links. NR also provides full mobility support, which is an important reliability aspect, not only for devices that are moving but also for stationary devices in a changing environment.

As mentioned, since the NR over-the-air transmissions in both UL and DL are centrally scheduled by the gNB, it can ensure radio resource efficiency, fairness of resource usage, and differentiated QoS treatment among applications and users. While in dynamic DL scheduling, transmission can be initiated immediately when DL data becomes available in the gNB, for dynamic UL scheduling, it is more complicated. If UL data arrives but no UL resources are yet assigned, the user equipment (UE) indicates the need for UL resources to the gNB via a scheduling request (SR) message and is subsequently assigned the needed resources for transmission. To avoid the latency introduced in the scheduling request loop, UL radio resources can also be pre-scheduled. In particular for periodical traffic patterns, as one would find in the critical communication use cases mentioned above, the pre-scheduling can rely on the UL configured grant (CG) feature. With this feature, periodically recurring UL resources can be preassigned for a device. Many of these configurations are supported in parallel, to serve multiple parallel UL traffic flows on the same device. An example is an industrial robot with multiple servo engines, sensors, and a camera connected via the same 5G IoT device to the system. In this case, besides time-critical data, other non-critical data (for example video or updates) needs to be transmitted too, from time to time.

Industrial Automation IoT Support

5G includes features to support Industrial IoT use cases, for which requirements have been collected by 5G-ACIA in [4]. For example, configured as a non-public network (NPN) deployment 5G can provide network services to a defined organization and its premises, such as a factory deployment. By this isolation, quality of service requirements, as well as security requirements can be achieved. Integration with a public network, if required, is however possible. Furthermore, 5G supports the integration with TSN. The main objective of TSN is to provide guaranteed data delivery within a guaranteed time window, i.e. bounded low latency.  IEEE 802.1 TSN [5] is a set of open standards that provide features to enable deterministic communication on standard IEEE 802.3 Ethernet. TSN standards can be seen as a toolbox for traffic shaping, resource management, time synchronization, and reliability – for which 5G supports the necessary supporting mechanisms. The basic idea of TSN integration is that the 5G system acts as a virtual bridge and transports the TSN Ethernet frames, adapts itself to the network settings of the TSN network, and implements required interfaces (e.g. application function (AF)) towards the TSN controller functions such as the centralized network configuration (CNC). Device-side and network-side TSN translator functions (DS-TT and NW-TT) are defined to convert the traffic and its requirements between TSN and 5G protocols. An illustration of this integration can be seen in Figure 2.

Figure 2: 5G TSN integration.

Figure 2: 5G TSN integration.

One interesting 5G feature is hereby the support for time synchronization, which is an essential part of TSN where a common absolute time reference is shared by all TSN network entities. NR supports accurate reference time synchronization in 1us accuracy level. Since NR is a scheduled system, an NR UE and a gNB are tightly synchronized to their OFDM symbol structures. A 5G internal reference time can be provided to the UE via broadcast or unicast signaling, associating a known orthogonal frequency division multiplex (OFDM) symbol to this reference clock. The 5G internal reference time can be shared within the 5G network, i.e., radio and core network components. This enables the support of TSN-based time synchronization with IEEE 802.1AS generalized precision time protocol (gPTP) [6], which relies upon that the 5G system at UE and network side are internally synchronized.  

Concluding Remarks

5G NR is equipped to reach the challenging requirements of time-critical IoT communication use cases from the areas of real-time media and AR applications, remote driving, and advanced industrial control systems.

References

  1. 3rd Generation Partnership Project, 3GPP TS 38.300 v16.5.0, NR and NG-RAN overall description, March 2021, [link]
  2. F. Alriksson, L. Boström, J. Sachs, Y.-P. E. Wang, A. Zaidi, Critical IoT connectivity: Ideal for time-critical communications, Ericsson technology review, June 2020, [link]
  3. T. Dudda, A. Shapin, A technical overview of time-critical communication with 5G NR, Ericsson blog, February 2021, [link]
  4. 5G Alliance for Connected Industries and Automation, 5G for Connected Industries and Automation (Second Edition), Whitepaper, March 2019, [link]
  5. 5G Alliance for Connected Industries and Automation, Integration of 5G with Time-Sensitive Networking for Industrial Communications, Whitepaper, April 2021, [link]
  6. I. Godor et al., "A Look Inside 5G Standards to Support Time Synchronization for Smart Manufacturing," in IEEE Communications Standards Magazine, vol. 4, no. 3, pp. 14-21, September 2020.

 

Torsten DuddaTorsten Dudda is a Master Researcher at Ericsson located in Aachen, Germany. He contributes to the radio architecture and protocol design of 5G NR, working closely with 3GPP standardization teams. His current research focuses on evolving the 5G NR support for critical communication use-cases such as Industrial IoT. Torsten Dudda joined Ericsson in 2012. He graduated with a diploma in electrical engineering and information technology from RWTH-Aachen University, Germany.

 

 

The Internet of … What ??!

Nahum Gershon
May 18, 2021

 

Suzanne Simard discovered that “fungal threads link nearly every tree in a forest — even trees of different species. Carbon, water, nutrients, alarm signals and hormones can pass from tree to tree through these subterranean circuits."

“Resources tend to flow from the oldest and biggest trees to the youngest and smallest.”

Chemical alarm signals generated by one tree prepare nearby trees for danger. Seedlings severed from the forest’s underground lifelines are much more likely to die than their networked counterparts. And if a tree is on the brink of death, it sometimes bequeaths a substantial share of its carbon to its neighbors.”  The Social Life of Forests, By Ferris Jabr, New York Times Magazine [1].

When I first read this article, I asked myself what would be an appropriate term to describe the situation? Is this a network of trees? Could one say that it is a kind of an “internet” of trees? Certainly, the complex environment does have some kind of a network or assembly of plants, but it could not be fully represented by a traditional simple word, “network”, or visually by a network diagram (containing only nodes and lines). Yes, the trees are connected but the connection is complex. Connections include sending and receiving signals, exchanging various resources (e.g., chemicals) while each plant (a tree or a fungal thread) has some degree of knowledge, self-perception, and ability to act. This ability of forests that have existed for millennia is quite different from the comparatively simple situation in some of my home Internet of Things networks…

Far from the Forest – My IoT Life at Home

Since I like to experiment (i.e., play) with technology, I have some camera sensors that are distributed around and inside my house. Each one of these cameras is positioned at a different location so it has its own area of view. The sensors are not directly connected to each other but rather, they send their signals to a central location - one sensor typically does not know what the other ones are doing. Moreover, unlike the situation with the social life of forests described above, the information coming out from the cameras around & inside my house is not synthesized or even fully understood in situ but rather sent to a central location and signals are sent to me through occasionally annoying series of beeps and messages. The synthesis of the information and its interpretation is done in my brain. Centrally. So, the sensors do not typically collaborate with one another directly by themselves.

Moving, But What?

On the other hand, these sensors could determine the motion of objects in their field of view. Most of the time, I get warnings that something is moving caused by a squirrel or even worse by a branch moving in the wind. These false alarms could sometimes have an effect similar to the one described in Aesop's Fables “The Boy Who Cried Wolf”… It would have been beneficial and practical if the cameras could identify the moving object – an animal, a person, certain people like the owner & family. It could get even worse. When the squirrel exits the coverage area of one camera and enters the coverage area of the next camera, I get another warning…

In spite of its weaknesses stated above, most of the time, I really enjoy having the IoT network outside and inside my house. Lights could be turned on and off remotely manually or through motion sensors. I get alerts when people enter my yard and I could even see when mail is being delivered and if the delivery person lays down the package by the door or as it happened before, tosses the package from a distance of 3 meters…

The Internet of Things

The situation around my home does not contradict the typical definition of the Internet of Things. According to the Wikipedia [2] “The Internet of things (IoT) describes the network of physical objects—'things’—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet.”  This IoT definition does not say that the IoT has to measure or transmit something useful and it does not address the potential interference of the technology (of the connection and the data exchange) with the values measured or with our way of life. It also does not require the individual sensors to be cognizant of the meaning of their measurements and to perceive what other sensors are doing. To reduce the widespread existence of “dumb” networks that just generate and distribute data without adding value or even confuse users, maybe we need to modify the definition of IoT to include understanding and relevance – just “connecting and exchanging data” is not enough.

We should also realize that not all assemblies of objects and sensors are the same - the above-mentioned case of trees in the forest, for example, is quite different from the assemblies of sensors at my home.  Thus, it could be misleading to use one term (e.g., network or Internet) to describe all of the possibilities of assemblies and objects. Using one word might imply that these objects and networks are the same or at least very similar. This might encourage oversimplified thinking and thus could affect our understanding of their capabilities and potential.

Trees, Sensors, and Now, Humans…

After thinking about the social life of forests and the IoT elements around my home, I was wondering if humans could “join this  crowd” or, in other words, how about humans with embedded sensors? Before we have sensors widely implanted inside us and on our skin, or having an interface between the Internet with our brain waves, we have already the mobile phone that is typically with us most of the day (and in many cases during the night). The mobile phone is connected to the Internet and has a number of sensors in it. This has been an opportunity for humans to become more central in the Internet sphere. It calls for a radically new paradigm, that has been named the Internet of People (IoP), “where the humans and their personal devices are not seen merely as end-users of applications, but become active elements of the Internet” [3].

Including humans in this “mix” of devices and applications calls for an upgrade of the concept of the “Internet” or for using different terms to describe different kinds of “crowds” and interactions. Meeting somebody, for example, is much more complex than just bringing two sensors together to close proximity. It is the human connection that could evoke feelings, enabling the interchange of various signals (words, visual cues, and feelings) and create what is called human moments [4]. Another example of the difference is the complexity of describing meetings and virtual meetings and what to do to make them effective [5,6].

Virtual Meetings

The transition to a system where the human user is integrated with technology is not always straightforward. For example, most of us are working from home these days during the COVID-19 pandemic. This has prevented us from meeting our colleagues, relatives, and friends face-to-face but rather we meet remotely using the Zoom platform or other equivalents. These meeting environments are assemblies of technology (sensors, computing devices, Internet, etc.) and humans.

Humans are not like sensors or objects that one could simply transport them from place to place, aggregate them, and simply connect them. Humans sense each other and their perceptions and behavior are affected by their human and non-human environments.

In meetings, for example, especially in virtual meetings, it is important how one starts, conducts, and ends the meeting [6]. It is also important that the audience participates in the meeting and that its members do not multi-task [5,6]. Another way for creating togetherness is to use specific interactive visuals and rituals as is described in [7]. This has no simple parallel in the physical sensor world… 

Asking Questions to Encourage Thinking Outside the Box

Using the same term (like the Internet of …) to describe vastly different types of assemblies might give us the wrong perception that they all behave the same. This is why when hearing the expression “The Internet of Things” or “The Internet of …”, it could be beneficial to ponder about it and ask ourselves questions like: “The Internet of What?!!” or even: “What Internet?!!”

References

  1. “The Social Life of Forests”, By Ferris Jabr, New York Times Magazine, https://www.nytimes.com/interactive/2020/12/02/magazine/tree-communication-mycorrhiza.html
  2. Internet of Things https://en.wikipedia.org/wiki/Internet_of_things
  3. Marco Conti, Andrea Passarella, Sajal K.Das, "The Internet of People (IoP): A new wave in pervasive mobile computing”, Pervasive and Mobile Computing, Volume 41, October 2017, Pages 1-27
  4. Anne-Laure Fayard, John Weeks, and Mahwesh Khan, Designing the Hybrid Office - From workplace to “culture space", Harvard Business Review, March-April 2021 https://hbr.org/2021/03/designing-the-hybrid-office
  5. Steven G. Rogelberg, “The Surprising Science of Meetings: How To Lead Your Team To Peak Performance”, Oxford University Press, 2019.
  6. Karin M. Reed and Joseph A. Allen, "Suddenly Virtual: Making Remote Meetings Work”, Wiley, 2021.
  7. Ulrik Ramsing, BlueBehavior, "Rethinking rituals to create team togetherness”, Klaxoon webinar, led by Charles Kergaravat https://www.youtube.com/watch?v=ZP2_eDHRAxE

 

nahum gershonNahum Gershon focuses on social media, the Internet of Things, strategic planning, visualization, combining creative expressions with technology and real-time information delivery, presentation & interaction (including storytelling) in mobile, wearable as well as traditional devices including how they could improve both organizational environments and our personal lives. He likes to play with ideas, words, and real devices. Nahum Gershon has served in many capacities at the IEEE over the years, in schmooz.org, and as a Senior Principal Scientist at the MITRE Corporation. Nahum is a well-known community organizer, mentor, and communicator and is quite socially oriented. He has a significant international & multicultural background (citizen of the world, speaking a number of languages) and is right and left brain enabled. He enjoys life!

 

 

Our Stealthy Housemates: Consumer IoT Devices, Privacy Risks, and Potential Mitigations

Anna Maria Mandalari, Hamed Haddadi, Daniel J. Dubois, and David Choffnes
May 18, 2021

 

Consumer Internet of Things (IoT) devices are gaining an increasing presence in our homes, with the promise to deliver unprecedented benefits and personalized services. The increasing range of sensors embedded in these devices, alongside the availability of sophisticated AI models and interactions mechanisms (e.g., voice-based smarthome assistants), present a complex range of functionality, analytics, and capabilities. However, this complexity results in our inability to fully assess and establish the reliability and trustworthiness of these devices, in addition to their security threats and privacy risks, despite our increasing dependence on these devices and their underlying services.

Today, we have an urgent need to develop appropriate security standards and practices, alongside methods to contain the privacy risks from IoT platforms. This requires a dialogue between the key industry players, privacy/security researchers, regulators, and user groups. The purpose of this article is to raise more questions than answers to initiate further discussions, and to highlight areas where further research might be pertinent.

Current Concerns

Typically, IoT devices have access to private information, be it personal consumer data or proprietary enterprise data. Consequently, various contractual agreements and trust boundaries need to be established between the users and the data operators, in addition to both parties’ reliance on the correct operation of each device. There are several concerns with IoT devices which serve to highlight the difficulties and complexities with the notion of trustworthiness in this setting, and also provide a good example of why more thought is required for future technologies.

IoT Devices Destinations: our study on 81 IoT devices in US and UK [1] demonstrates that 56% of the devices in US and 84% in UK contact at least one destination abroad. The below Sankey diagram (Figure 1) shows that most of the traffic is produced by cameras and televisions which contact countries outside of these devices’ privacy jurisdictions.

Figure 1: Volume of network traffic between devices in US (left) and UK (right) to the top 7 destination regions (center), grouped by category (middle left and right).

Figure 1: Volume of network traffic between devices in US (left) and UK (right) to the top 7 destination regions (center), grouped by category (middle left and right).

Third Party Destinations: more than 50% of destinations contacted by the IoT devices are not first parties, i.e., not the manufacturer, or a related company responsible for fulfilling the device functionality. Third party destinations could be trackers and advertisers. Moreover, many devices (89%) are vulnerable to at least one activity of inference that can be used to identify unexpected activities (Figure 2) [2].

Figure 2: Examples of unexpected behavior from consumer IoT devices.

Figure 2: Examples of unexpected behavior from consumer IoT devices.

 

Existing Third Party Blocker Systems: existing approaches block destinations for advertising and tracking services using blocklists [3], but destinations on those blocklists are mostly assessed for various web trackers, thus missing non-required destinations for consumer IoT devices [4].

Regulations: in theory, the GDPR in the EU and CCPA in California are designed to provide a regulatory framework for data protection and privacy. This in turn should encourage the manufacturers to demonstrate to consumers that they adhere to the regulations and hence engender trust. From a geopolitical perspective, however, considering the ubiquitous nature of the interconnected devices, current regulations’ enforcement and coverage might not be enough. Particularly:

  • there is a lack of understanding regional differences in regulations [5], e.g., GDPR is mostly adopted in the EU;
  • there are issues around legacy devices, where a manufacturer is out of business, leaving devices unable to receive software patches and security updates.

Challenges and Mitigations

Considering all the reasons listed above, there is a need for an automated framework for detecting and isolating all non-essential communications from IoT devices, ideally on the user’s premises. Such a framework can rely on a number of data points for allowing and blocking certain destinations:

Characterizing Network Traffic: IoT devices are often easily recognizable from their network traffic profile [6]. However, devices’ network profile changes over time due to firmware upgrade, the setup of a new device on the same network, or usage patterns variation.

MUD Profile: the Manufacturer Usage Description (MUD) [7] profile specifies which destinations the device is allowed to contact. Despite various standardization efforts, however, MUD profiles still remain largely unused by device manufacturers.

Figure 3: Characterize functional vs non-functional destinations.

Figure 3: Characterize functional vs non-functional destinations.

Blocking Non-essential Traffic: since the vast majority of IoT traffic is encrypted, it is often hard to quantify the data leakages. One approach for mitigating the exposure of information is to automatically block any connections that are not essential for the proper functioning of a device (Figure 3). If a device still works after blocking a destination, that destination is unlikely to be essential to the functionality of the device, and blocking it might limit excessive data sharing. The complexity of the current Internet network infrastructure poses hard challenges for separating critical and non-essential traffic for the overall operation of IoT devices. Using extensive testbeds, automated experiments, crowdsourcing approaches, and in-situ user studies, we can shed more light on the peculiar interactions between the IoT devices, their manufacturers, and the users [4]. This is a first step towards limiting the privacy and security risks posed by these devices.

References

  1. J. Ren, D.J. Dubois, D. Choffnes, A.M. Mandalari, R. Kolcun, and H. Haddadi, “Information Exposure for Consumer IoT Devices: A Multidimensional, Network-Informed Measurement Approach". Proc. of the Internet Measurement Conference (IMC) 2019.
  2. D. J. Dubois, R. Kolcun, A.M. Mandalari, M.T. Paracha, D. Choffnes, and H. Haddadi, “When Speakers Are All Ears: Characterizing Misactivations of IoT Smart Speakers". Proc. on Privacy Enhancing Technologies Symposium 2020.
  3. “Pi-Hole: a Black Hole for Internet Advertisements". https://pi-hole.net/.
  4. A.M. Mandalari, D.J. Dubois, R. Kolcun, M.T. Paracha, H. Haddadi, and D. Choffnes, “Blocking without Breaking: Identification and Mitigation of Non-Essential IoT Traffic". Proc. on Privacy Enhancing Technologies Symposium 2021.
  5. S. Sirur, J. R. Nurse, and H. Webb, “Are We There Yet?: Understanding the Challenges Faced in Complying with the General Data Protection Regulation (GDPR)". Proc. of the 2nd International Workshop on Multimedia Privacy and Security 2018.
  6. S. J. Saidi, A.M. Mandalari, R. Kolcun, H. Haddadi, D.J. Dubois, D. Choffnes, G. Smaragdakis, and A. Feldmann, “A Haystack Full of Needles: Scalable Detection of IoT Devices in theWild". Proc. of the Internet Measurement Conference (IMC) 2020.
  7. E. Lear, R. Droms, D. Romascanu, “RFC 8520-Manufacturer Usage Description Specification". https://tools.ietf.org/html/rfc8520.

 

Anna Maria MandalariAnna Maria Mandalari is a Research Associate in the Dyson School of Design Engineering at the Faculty of Engineering at Imperial College London. Her research interests are related to IoT, privacy, and Internet protocols.

 

Hamed Haddadi2Hamed Haddadi is an Associate Professor at Imperial College. He is a Security Science Fellow of the Institute for Security Science and Technology and of the Data Science Institute. He is also a Visiting Professor at Brave Software where he works on developing privacy-preserving protocols.

 

Daniel J DuboisDaniel J. Dubois is an Associate Research Scientist at Northeastern University, his research is rooted in software engineering, with a current focus on IoT privacy. He maintains the Mon(IoT)r Lab testbed, which provides an IoT monitoring infrastructure to four research institutions.

 

David ChoffnesDavid Choffnes is an Associate Professor at Northeastern University, member of the Cybersecurity and Privacy Institute, and affiliate faculty at the Center for Law, Innovation and Creativity (CLIC).