Article 1

SmartTags-enabled Fast-Moving Consumer Goods: Creation and Management

Suparna De and Nenad Gligoric

New types of sensors that are printable and can collect, sense, and read environmental parameters of relevance to the product and its use are becoming reality. For fast-moving consumer goods (FMCG) this represents the basis for the creation of a new generation of supply chains which, in combination with GS1 Digital Link global specifications standard, makes it possible to identify each product item, track it and monitor it on an item level.

 


Article 2

Smart Building PLC Testbed Leveraging IoT Network Technologies

Vaishnavi Rajini Mohan, Krunal Patel, Manoj Kumar, Ramkrishna Pasumarthy, and Paventhan Arumugam

IEEE 1901 standard for narrowband Power Line Communications (PLC) over indoor and outdoor electrical wiring supports data rates of up to 500 kb/s. Also, recent amendments like IEEE 1901a-2019 provides enhancements for the Internet of Things (IoT) applications.

 


Article 3Bridging the Digital Divide Using Personalized Service Level Agreements in the Internet of Things

Cathryn Peoples

TThe digital divide lives on in 2020 and many who could benefit from the Internet of Things (IoT) technology are simply not able to. Consider the elderly population as an example - almost half of the over 75s do not even use the Internet, never mind the IoT. This creates a problem in the modern world, given the range of services that are only being made available in an online capacity through the IoT.

 


Article 4Artificial Intelligence Leverages 3-layer IoT Architectures for the Next Industrial Revolution

Jacobo Fanjul, Álvaro González-Vila, Jose Ramón Juarez, and Josu Bilbao

Over the last years, the industrial ecosystem has experienced a paramount transformation. Significant research efforts have been devoted to optimizing and enriching Industry resources through advanced Artificial Intelligence (AI) tools. Obstacle detection, predictive maintenance, and quality control are well-known examples of the productivity improvements that AI yields for automotive, transportation, and cyber-physical manufacturing systems.

 

 

EVENTS & ANNOUNCEMENTS


Article 5

IEEE Internet of Things Initiative - Upcoming Events

IEEE 7th World Forum on Internet of Things - 2021
Submit a paper or proposal today.
Sign up to be a Technical Paper Reviewer.

IEEE IoT Vertical and Topical Summit focused on "Wireless Sensing, with Wireless Sensors, in Wireless Sensor Networks for IoT Applications (WS3NI)”
Plan to attend this virtual Summit in January 2021.

IEEE IoT Initiative Session titled "Advances in IoT Technologies and Applications" at IEEE RAICS 2020.
Mark December 5th on your calendar and register today.


Article 5

IEEE Internet of Things Magazine

Internet of Things Magazine logo The Internet of Things Magazine (IoTM) publishes high-quality articles on IoT technology and end-to-end IoT solutions. IoTM articles are written by and for practitioners and researchers interested in practice and applications, and selected to represent the depth and breadth of the state of the art. The technical focus of IoTM is the multi-disciplinary, systems nature of IoT solutions.

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


Article 5

IEEE IoT/SA Smart Cities Survey

IEEE is reaching out to cities worldwide that have important smart city experience in order to create a new global smart cities & technology alliance. Make an impact on behalf of your city by completing the survey. Take the survey!

 

This Month's Contributors

Suparna De is a Senior Lecturer in Computer Science and Networks at the University of Winchester, UK. She obtained her Ph.D. in Electronic Engineering from the University of Surrey.
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Nenad Gligoric is one of the pioneers of the IoT scene in Serbia, working as a software engineer in Ericsson and as a project manager in DunavNET on more than 10 EU, FP7 and H2020 projects.
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Vaishnavi Rajini Mohan is an intern at IITM / ERNET working on the project Smart  Building PLC Testbed leveraging  IoT network technologies.
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Krunal Patel is an Embedded Product Architect and Manager with over 14+ years of developing embedded products from concept to functional prototypes.
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Manoj Kumar is Director of System Research and Applications at STMicroelectronics, India providing a worldwide mission to build and support reference designs and system solutions in the areas of Connectivity (BLE, Sub GHz, Power Line Communication), Metering, Motor Control, Power & Lighting, and IoT.
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Ramkrishna Pasumarthy is an associate professor at the Department of Electrical Engineering, and the Robert Bosch Center of Data Science and AI IIT Madras India.
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Paventhan Arumugam is Director of R&D at ERNET India (under Ministry of Electronics & IT) who is also chair of the IEEE-SA industry connections activity on PLC Testbed in India.
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Cathryn Peoples received a B.A. degree in business studies with computing, an M.Sc. degree in telecommunications and internet systems, and a Ph.D. degree in networking from Ulster University, U.K., in 2004, 2005, and 2009, respectively.
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Jacobo Fanjul received his Telecommunication Engineering (M.Sc.) degree from the University of Cantabria, Santander, Spain, in 2014.
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Álvaro González-Vila received his M.Sc. degree in Telecommunication Engineering in 2014 from the University of Cantabria, Spain.
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Jose Ramón Juarez received his M.Eng. degree in Telecommunication Engineering in 2004 from the University of the Basque Country (UPV/EHU), Spain.
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Josu Bilbao (IEEE Senior Member) obtained the Telecommunication Engineering degree from the Faculty of Engineering of Bilbao (UPV/EHU), the M.Sc. degree in Communications and Control from the University of the Basque Country (UPV/EHU), and the Ph.D degree in Computer Science from the University of Navarra.
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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.

Bridging the Digital Divide Using Personalized Service Level Agreements in the Internet of Things

Cathryn Peoples
November 11, 2020

 

The digital divide lives on in 2020 and many who could benefit from the Internet of Things (IoT) technology are simply not able to. Consider the elderly population as an example - almost half of the over 75s do not even use the Internet, never mind the IoT. This creates a problem in the modern world, given the range of services that are only being made available in an online capacity through the IoT.

Cost efficiencies can be achieved through operating such business models, but without all potential users on board with the approach, it is not one that can be exploited. The more traditional, paper-based approaches, therefore, need to continue to be used instead.

Why is this the situation we live in today? Why does the digital divide persist when internet capability is a critical backbone of society? One important reason is the complexity of service setup processes - several would-be users, making particular reference to those who are older, do not have the mental and/or physical capacity to establish a connection to online services. This is not only applicable to citizens who grew up without the internet, but also for those who used online technologies and services in their earlier lives – the evidence suggests that capacity to use technology declines with age, as discussed in [1]. Service setup procedures are largely manual, and interaction is required with a service provider to establish a connection; this is prohibitive for users without technical awareness or expertise.

Another reason for a lack of connection to the IoT is the financial cost of service provision. To participate in the online world, it is necessary to have at least one online device, which may have required a setup connection cost, in addition to either a monthly or pay as you go subscription rate. In relation to maintaining a connection, there is generally a limited range of services that customers may purchase - from an individual provider, there may only be three service tiers. In saying that IoT services are tiered, this refers to the fact that there can be different service packages available from ISPs, each of which varies in the quality of the service provided, the responsiveness of the support team, and the associated cost; a selection of these are summarised in [2] (Table 3). Customers, however, could have more widely-varying service needs than can be responded to using a restricted number of service tiers. It could therefore be natural to assume that there will be a similarly diverse set of service provisions to enable them to access the IoT in a manner that suits their needs. This, however, is not the case.

As a result, research has begun by the author to optimize the service provisioning process, through automating service setup and making services available which are tailored more closely to customer needs. The proposal is to achieve this by taking into account a selection of personal user characteristics, which are subsequently used to influence the service provisioned in ways not defined before. These personal characteristics capture detail on a customer’s tolerance of ad hoc changes to their service provision. This allows cost efficiencies to be exploited, which is an important factor in helping to bridge the digital divide.

With the customer tolerances known, the intention is to use these when considering service provision and management. Quality of Service is the aspect traditionally taken into account when defining service agreements, with an assumption that a customer will have subscribed to a service that meets their needs - if the level of service promised is provided, the needs of the customer will be responded to. However, depending on individual personal characteristics, customers can tolerate lower Quality of Service than is provisioned in the SLA. This is information that can be exploited in the service provisioning process, yet is not done at present.

In support of this mode of operation, it is therefore proposed that the process of service provision and management is achieved using a data ontology designed for the IoT – the model proposed in this research will be published in January 2021 [3]. An ontology in general describes a hierarchy of attributes, with leaves branching from higher sections of the tree in association with each category of data. Many ontologies for the IoT exist. However, the limitations, as discussed in [3], include that each ontology is typically provisioned for a specific domain or to respond to a particular operational challenge; a single ontology addressing the needs of all scenarios across the IoT does not exist. It is therefore to this gap which our work responds.

The objective of the ontology proposed is to allow sufficient data to be collected such that a Service Level Agreement (SLA) can be provisioned which fulfills customer needs. The proposed ontology captures Customer, Device, Attribute, Dataset, and SLA branches, with leaves including Risk (true/false) from the Customer perspective, and Interruptible (true/false) from the Attribute perspective. Both of these metrics can be used to identify if a customer can cope with a somewhat disrupted service – cost efficiencies can be applied for more flexible customers, matching their tolerances with the service provisioned, as opposed to the more traditional Quality of Service expectations. This approach applies a more personalized strategy to SLA provisioning.

The personalized SLA will be customized in both the service which a customer can tolerate, in the worst-case scenario, in addition to a service that a customer can financially afford. When a customer wants a completely reliable service under this model, they must expect the associated cost overhead, without efficiencies, to be exposed to this. When the customer can tolerate a less than perfect service, they can benefit from the cost efficiencies as a result of possible inconvenience, albeit an inconvenience they can cope with and have agreed to.

The digital divide exists where citizens want to access services, but are unable to. Thinking about our focus population, the elderly, we can remember that just because older users are not online, this doesn’t mean that their desire is not there. They are effectively excluded from a significant aspect of our society today, and the evidence suggests that this is having a negative mental impact, as discussed in [1]. Not being able to afford a service is one thing, but being able to afford it yet being unable to access it is another. There is an opportunity to adapt how services are provisioned so that the value which results from participating overcomes the costs - practical and financial - that are involved in setting a service up, and it is to this which the author’s research seeks to contribute.

This work is being carried out at the BT Ireland Innovation Centre in a partnership between BT and Ulster University as part of a five-year project, funded by Invest Northern Ireland [4][5].

References

  1. Peoples, C., Moore, A. and Zoualfaghari, M. (2020). A Review of the Opportunity to Connect Elderly Citizens to the Internet of Things (IoT) and Gaps in the Service Level Agreement (SLA) Provisioning Process. EAI Endorsed Transactions on Cloud Systems, 6(18), 1-8.
  2. Peoples, C., Rabbani, K., Abu-Tair, M., Wang, B., Morrow, P., Moore, A., Rafferty, J., McClean, S., Zoualfaghari, M. H. and Kulkarni, P. (2019). A Review of IoT Service Provision to Assess the Potential for System Interoperability in an Uncertain Ecosystem. IEEE SmartWorld, 1964-1971.
  3. Ed. Khan, M. A., Algarni, F. and Tabrez, M. (2021). Smart Cities: A Data Analytics Perspective. Available at: https://bit.ly/368WXxC.
  4. BT Ireland Innovation Centre Homepage. Available at: https://bit.ly/2GDN7Lv.
  5. BT. (2017). BT Chooses Northern Ireland for £28.6 million innovation centre and creation of 50 graduate jobs. Available at: https://bit.ly/2JPICih.

 

Cathryn PeoplesCathryn Peoples received a B.A. degree in business studies with computing, an M.Sc. degree in telecommunications and internet systems, and a Ph.D. degree in networking from Ulster University, U.K., in 2004, 2005, and 2009, respectively. She is currently employed as a Research Associate at Ulster University working on Internet of Things (IoT) research. Cathryn is also employed by The Open University in the School of Computing and Communications within the Faculty of Science, Technology, Engineering & Mathematics as an Associate Lecturer in Software Engineering. She became the co-Editor-in-Chief of the EAI Endorsed Transactions on Cloud Systems in January 2020. Her research interests include cloud management, cross-layer protocol optimization, delay-tolerant networking, smart cities, and green IT.

 

 

Artificial Intelligence Leverages 3-layer IoT Architectures for the Next Industrial Revolution

Jacobo Fanjul, Álvaro González-Vila, Jose Ramón Juarez, and Josu Bilbao
November 11, 2020

 

Over the last years, the industrial ecosystem has experienced a paramount transformation. Significant research efforts have been devoted to optimizing and enriching Industry resources through advanced Artificial Intelligence (AI) tools. Obstacle detection, predictive maintenance, and quality control are well-known examples of the productivity improvements that AI yields for automotive, transportation, and cyber-physical manufacturing systems.

The reliability and performance of communications in these environments are even more critical for simultaneous dense dataflows, telemetry acquisition, and security policy compliance [1, 2]. Despite the massive computational capabilities of Cloud infrastructures, real-time applications are also constrained by roundtrip latency. Additionally, functional issues or anomalies at the Cloud side would lead to a set of disconnected IoT endpoints with no means to carry out their corresponding tasks.

In parallel to purely technical limitations, economical aspects need to be considered when evaluating the potential disadvantages of conventional Cloud approaches for industrial scenarios. In particular, the cost of lower communication performance, connectivity impairments, or Cloud failure is several orders of magnitude higher than in the case of average user applications [3].

In this regard, the 3-layer IoT paradigm brings Intelligence down to the Edge to overcome the most relevant drawbacks of conventional Cloud architectures. We focus on the remarkable benefits that can be achieved by IoT-Edge-Cloud deployments in three scenarios described hereinafter.

Figure 1: Example of 3-layer architecture for the Industrial IoT (IIoT).

Figure 1: Example of 3-layer architecture for the Industrial IoT (IIoT).

 

The ever-growing public transportation networks for large metropolitan areas imply the transmission of vast amounts of data, associated with the implementation of obstacle detection techniques, scheduling, and user-side timetable tracking, among others. Specifically, the EU-funded ELASTIC Project [4] addresses the challenges of data analytics across the Florence tramway network. As abovementioned, advanced AI techniques require massive data acquisition, and hence the performance of a 2-tier IoT-Cloud strategy would be compromised. For this reason, the computational resources are distributed, with AI-enabled Edge devices deployed at tramway vehicles.

The acquired videos, GPS, and sensor samples cannot be entirely transmitted towards the Cloud, given that WLAN connectivity is only guaranteed at tram stops and LTE coverage could be limited at several points across the line. On the contrary, the software architecture provides the system with a distributed data analytics platform capable of performing highly demanding computational tasks at the Edge. Analogously, data storage and accessibility are also handled by a distributed database [5]. Consequently, a set of non-functional requirements (NFR) need to be fulfilled in such a way that efficiency, data coherence, and robustness is ensured across the network. For this purpose, additional tools are included to monitor real-time attributes, energy consumption, cybersecurity, and communication latency [6]. Whenever one or more of these parameters falls out of scope, the NFR tool indicates the orchestrator [7] to re-schedule computational loads among the different Edge devices, in such a way that the entire system keeps working as expected.

On the other hand, many applications in the Industry sector require an entire fleet of connected devices to be managed. One of the main aspects to consider in such cases is software version control and updates. When the number and location diversity of devices scales, on-site manual updates are not feasible, and therefore more sophisticated approaches are developed. A remarkable example is the software version control toolchain within the context of the Arrowhead Tools EU-funded Project [8]. The idea behind this solution is to carry out a sequence that checks the current versions of the software tools running on every device in the system. The Edge devices report the obtained versions whereas, on the other hand, the most recent available versions and requirements are listed in the Cloud. Back at the Edge layer, every device ensures that the requirements for new versions are fulfilled, and if so, pull the new versions for validation. When the validation tests are successful, then the new versions are deployed. In short, the update procedure can be executed with more information about the corresponding devices, and validation tasks are offloaded from Cloud to Edge and performed over real deployments remotely.

Also, 3-layer schemes enhance field monitoring and validation for control networks in cyber-physical systems [9]. For instance, as one of the use-cases in the ADEPTNESS project [10], a control area network (CAN) bus connecting several IoT devices can be monitored from an Edge node. Then, regarding a given specification, relevant functional variables are reported periodically in such a way that normal operation of the system is continuously tracked. With this information, any outlying behavior would be detected. Furthermore, the monitoring specification and any other application running on the Edge endpoints can be updated and validated in a distributed, transparent manner, i.e., following the continuous integration/continuous deployment (CI/CD) lines [11].

As an outcome, industrial markets such as smart elevation, railway transportation, and manufacturing can benefit from switching to multilevel distributed approaches on a very short-term basis. These 3-layer IoT-Edge-Cloud architectures play a crucial role when transferring the aforementioned advances towards Industry 4.0.

References

  1. H. Chaouchi, T. Bourgeau, “Internet of Things: Building the New Digital Society,” IoT, vol. 1(1), pp. 1-4, June 2018.
  2. P. Li, J. Su, X. Wang, “iTLS: Lightweight Transport Layer Security Protocol for IoT with Minimal Latency and Perfect Forward Secrecy,” IEEE Internet of Things Journal, vol. 7(8), pp. 6828-6841, April 2020.
  3. M. Yao. in Forbes (2017, Apr. 14). 4 Unique Challenges Of Industrial Artificial Intelligence [Online]. Available: https://bit.ly/32spLQu
  4. ELASTIC: A Software Architecture for Extreme-Scale Big-Data Analytics in Fog Computing Ecosystems. European Union Horizon 2020 research and innovation programme, grant agreement no. 825473. Available: https://bit.ly/2U63Vhf
  5. J. Martí, A. Queralt, D. Gasull, A. Barceló, J. J. Costa, T. Cortes, “Dataclay: A distributed data store for effective inter-player data sharing,” Journal of Systems and Software, vol. 131, pp. 129-145, September 2017.
  6. A. Orive, A. Agirre, J. Bilbao, M. Marcos, “Passive Network State Monitoring for Dynamic Resource Management in Industry 4.0 Fog Architectures,” in 14th IEEE International Conference on Automation Science and Engineering (CASE), Munich, Germany, 2018, pp. 1414-1419.
  7. R. M. Badia, J. Conejero, C. Diaz, J. Ejarque, D. Lezzi, F. Lordan, C. Ramon-Cortes, R. Sirvent, “COMP Superscalar, an interoperable programming framework,” Software X, vol. 3-4, pp. 32-36, December 2015.
  8. Arrowhead Tools. ECSEL Joint Undertaking (JU) – European Union Horizon 2020 research and innovation programme and Norway and Switzerland, grant agreement no. 826452. Available: https://bit.ly/38q3Zkq
  9. G. Peralta, M. Iglesias-Urkia, M. Barcelo, R. Gomez, A. Moran, J. Bilbao, “Fog computing based efficient IoT scheme for the Industry 4.0,” in IEEE International Workshop of Electronics, Control, Measurement, Signals and their Application to Mechatronics (ECMSM), Donostia – San Sebastian, Spain, 2017, pp. 117-122.
  10. ADEPTNESS: Automating the design-operation continuum of Cyber Physical Systems of Systems. European Union Horizon 2020 programme for research, technological development and demonstration, grant agreement no. 871319. Available: https://bit.ly/2GGoxJP
  11. M. Shahin, M. A. Babar, L. Zhu, “Continuous Integration, Delivery and Deployment: A Systematic Review on Approaches, Tools, Challenges and Practices,” IEEE Access, vol. 5, pp. 3909-3943, March 2017.

 

Jacobo FanjulJacobo Fanjul received his Telecommunication Engineering (M.Sc.) degree from the University of Cantabria, Santander, Spain, in 2014. In 2013, he joined the Department of Communications Engineering, University of Cantabria, where he focused on advanced signal processing techniques for wireless communications. During 2016, he was a visiting researcher at the Department of Electrical Engineering and Computer Science (EECS), University of California, Irvine. Shortly afterwards, he was a visiting researcher at the Multimedia Communications Laboratory, the University of Texas at Dallas. In 2019, he received his Ph.D. in Information and Communication Technologies for Mobile Networks, and he joined IKERLAN Technology Research Centre (Basque Research and Technology Alliance, BRTA) as an R&D Engineer on IoT & Digital Platforms.

 

Alvaro Gonzalez Vila Álvaro González-Vila received his M.Sc. degree in Telecommunication Engineering in 2014 from the University of Cantabria, Spain. He then obtained his Ph.D. degree in Engineering Science and Technology in 2019 from the University of Mons, Belgium, being his research focused on advanced coatings for optical fiber sensors. He was the holder of a FRIA grant from the Belgian F.R.S.-FNRS from 2015 to 2019. During 2018, he was a visiting researcher at the Institute of Photonics Technology, Jinan University, Guangzhou, China. He is an Early Career Member of the OSA and SPIE. In 2020 he joined IKERLAN Technology Research Centre (Basque Research and Technology Alliance, BRTA) as an R&D Engineer on IoT & Digital Platforms.

 

Jose Ramon JuarezJose Ramón Juarez received his M.Eng. degree in Telecommunication Engineering in 2004 from the University of the Basque Country (UPV/EHU), Spain. He obtained his Ph.D. degree in 2011 from the Public University of Navarre, Spain, through the program “Technologies for distributed management of information”. During this period, he held an Assistant Lecturer position in the Computing Systems and Languages Department, and he was a member of the Distributed Systems Group at the Public University of Navarre, Spain. He was a visiting researcher at the University of Minho, Braga, Portugal, and at the University of Lugano, Switzerland. After working for several companies from the private sector, he is currently the leader of the IoT & Digital Platforms research group at IKERLAN Technology Research Centre. His main interests comprise high-availability systems, dynamic and adaptative distributed systems, machine learning, wireless communications, 5G, lightweight protocols, fog-edge-cloud architectures, and software analysis and testing.

 

Josu BilbaoJosu Bilbao (IEEE Senior Member) obtained the Telecommunication Engineering degree from the Faculty of Engineering of Bilbao (UPV/EHU), the M.Sc. degree in Communications and Control from the University of the Basque Country (UPV/EHU), and the Ph.D degree in Computer Science from the University of Navarra. He currently leads the ICT (Information and Communication Technologies) research department at IKERLAN, a private research center leader in technology transference and part of MONDRAGON Corporation. He leads the department composed of 2 research groups: “IoT & Digital Platforms” research group; and “Data Analytics & Artificial Intelligence” research group.
He plays an active role in different standardization committees and development of industrial products, and his current research interests span several fields such as IoT and IIoT, real-time CPS integration in the IoT, Cloud and Fog-based architectures, Artificial Intelligence, Edge computing and 5G among others.