Next Issue
Volume 3, June
Previous Issue
Volume 2, December
 
 

IoT, Volume 3, Issue 1 (March 2022) – 14 articles

Cover Story (view full-size image): The Internet of Things brings connectivity to everyday objects. These connected devices have to be managed considering their severe constraints in terms of energy, memory, processing, and communication. In this context, the OMA LWM2M protocol has been designed for remote device management, through a server usually deployed in the cloud. We propose the introduction of a LWM2M Proxy at the network edge, in between devices and servers, to improve various LWM2M procedures. Moreover, the Proxy enables the support of QoS-aware services through a set of extended functions to efficiently use resources at the edge, thus providing a reduced and more predictable end-to-end latency. We evaluate this solution both by simulation and experimentally, showing that it can thoroughly improve the performance of the system. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Select all
Export citation of selected articles as:
3 pages, 170 KiB  
Editorial
Editorial “Industrial IoT as IT and OT Convergence: Challenges and Opportunities”
by Carlo Giannelli and Marco Picone
IoT 2022, 3(1), 259-261; https://doi.org/10.3390/iot3010014 - 15 Mar 2022
Cited by 10 | Viewed by 3955
Abstract
During the last decade, the advent of the Internet of Things (IoT) and its quick and pervasive evolution have significantly revolutionized the Information Technology ecosystem [...] Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
40 pages, 833 KiB  
Article
Scheduling UWB Ranging and Backbone Communications in a Pure Wireless Indoor Positioning System
by Maximilien Charlier, Remous-Aris Koutsiamanis and Bruno Quoitin
IoT 2022, 3(1), 219-258; https://doi.org/10.3390/iot3010013 - 2 Mar 2022
Cited by 2 | Viewed by 5637
Abstract
In this paper, we present and evaluate an ultra-wideband (UWB) indoor processing architecture that allows the performing of simultaneous localizations of mobile tags. This architecture relies on a network of low-power fixed anchors that provide forward-ranging measurements to a localization engine responsible for [...] Read more.
In this paper, we present and evaluate an ultra-wideband (UWB) indoor processing architecture that allows the performing of simultaneous localizations of mobile tags. This architecture relies on a network of low-power fixed anchors that provide forward-ranging measurements to a localization engine responsible for performing trilateration. The communications within this network are orchestrated by UWB-TSCH, an adaptation to the ultra-wideband (UWB) wireless technology of the time-slotted channel-hopping (TSCH) mode of IEEE 802.15.4. As a result of global synchronization, the architecture allows deterministic channel access and low power consumption. Moreover, it makes it possible to communicate concurrently over multiple frequency channels or using orthogonal preamble codes. To schedule communications in such a network, we designed a dedicated centralized scheduler inspired from the traffic aware scheduling algorithm (TASA). By organizing the anchors in multiple cells, the scheduler is able to perform simultaneous localizations and transmissions as long as the corresponding anchors are sufficiently far away to not interfere with each other. In our indoor positioning system (IPS), this is combined with dynamic registration of mobile tags to anchors, easing mobility, as no rescheduling is required. This approach makes our ultra-wideband (UWB) indoor positioning system (IPS) more scalable and reduces deployment costs since it does not require separate networks to perform ranging measurements and to forward them to the localization engine. We further improved our scheduling algorithm with support for multiple sinks and in-network data aggregation. We show, through simulations over large networks containing hundreds of cells, that high positioning rates can be achieved. Notably, we were able to fully schedule a 400-cell/400-tag network in less than 11 s in the worst case, and to create compact schedules which were up to 11 times shorter than otherwise with the use of aggregation, while also bounding queue sizes on anchors to support realistic use situations. Full article
Show Figures

Figure 1

28 pages, 735 KiB  
Review
Conflict Detection and Resolution in IoT Systems: A Survey
by Pavana Pradeep and Krishna Kant
IoT 2022, 3(1), 191-218; https://doi.org/10.3390/iot3010012 - 28 Feb 2022
Cited by 13 | Viewed by 6987
Abstract
Internet of Things (IoT) systems are becoming ubiquitous in various cyber–physical infrastructures, including buildings, vehicular traffic, goods transport and delivery, manufacturing, health care, urban farming, etc. Often multiple such IoT subsystems are deployed in the same physical area and designed, deployed, maintained, and [...] Read more.
Internet of Things (IoT) systems are becoming ubiquitous in various cyber–physical infrastructures, including buildings, vehicular traffic, goods transport and delivery, manufacturing, health care, urban farming, etc. Often multiple such IoT subsystems are deployed in the same physical area and designed, deployed, maintained, and perhaps even operated by different vendors or organizations (or “parties”). The collective operational behavior of multiple IoT subsystems can be characterized via (1) a set of operational rules and required safety properties and (2) a collection of IoT-based services or applications that interact with one another and share concurrent access to the devices. In both cases, this collective behavior often leads to situations where their operation may conflict, and the conflict resolution becomes complex due to lack of visibility into or understanding of the cross-subsystem interactions and inability to do cross-subsystem actuations. This article addresses the fundamental problem of detecting and resolving safety property violations. We detail the inherent complexities of the problem, survey the work already performed, and layout the future challenges. We also highlight the significance of detecting/resolving conflicts proactively, i.e., dynamically but with a look-ahead into the future based on the context. Full article
Show Figures

Figure 1

22 pages, 4753 KiB  
Article
An Edge-Based LWM2M Proxy for Device Management to Efficiently Support QoS-Aware IoT Services
by Martina Pappalardo, Antonio Virdis and Enzo Mingozzi
IoT 2022, 3(1), 169-190; https://doi.org/10.3390/iot3010011 - 26 Feb 2022
Cited by 5 | Viewed by 5035
Abstract
The Internet of Things (IoT) brings Internet connectivity to devices and everyday objects. This huge volume of connected devices has to be managed taking into account the severe energy, memory, processing, and communication constraints of IoT devices and networks. In this context, the [...] Read more.
The Internet of Things (IoT) brings Internet connectivity to devices and everyday objects. This huge volume of connected devices has to be managed taking into account the severe energy, memory, processing, and communication constraints of IoT devices and networks. In this context, the OMA LightweightM2M (LWM2M) protocol is designed for remote management of constrained devices, and related service enablement, through a management server usually deployed in a distant cloud data center. Following the Edge Computing paradigm, we propose in this work the introduction of a LWM2M Proxy that is deployed at the network edge, in between IoT devices and management servers. On one hand, the LWM2M Proxy improves various LWM2M management procedures whereas, on the other hand, it enables the support of QoS-aware services provided by IoT devices by allowing the implementation of advanced policies to efficiently use network, computing, and storage (i.e., cache) resources at the edge, thus providing benefits in terms of reduced and more predictable end-to-end latency. We evaluate the proposed solution both by simulation and experimentally, showing that it can strongly improve the LWM2M performance and the QoS of the system. Full article
(This article belongs to the Special Issue Advanced Quality of Service Approaches in Edge Computing)
Show Figures

Figure 1

22 pages, 2774 KiB  
Article
Trajectory Planing for Cooperating Unmanned Aerial Vehicles in the IoT
by Emmanuel Tuyishimire, Antoine Bagula, Slim Rekhis and Noureddine Boudriga
IoT 2022, 3(1), 147-168; https://doi.org/10.3390/iot3010010 - 24 Feb 2022
Cited by 8 | Viewed by 4086
Abstract
The use of Unmanned Aerial Vehicles (UAVs) in data transport has attracted a lot of attention and applications, as a modern traffic engineering technique used in data sensing, transport, and delivery to where infrastructure is available for its interpretation. Due to UAVs’ constraints [...] Read more.
The use of Unmanned Aerial Vehicles (UAVs) in data transport has attracted a lot of attention and applications, as a modern traffic engineering technique used in data sensing, transport, and delivery to where infrastructure is available for its interpretation. Due to UAVs’ constraints such as limited power lifetime, it has been necessary to assist them with ground sensors to gather local data, which has to be transferred to UAVs upon visiting the sensors. The management of such ground sensor communication together with a team of flying UAVs constitutes an interesting data muling problem, which still deserves to be addressed and investigated. This paper revisits the issue of traffic engineering in Internet-of-Things (IoT) settings, to assess the relevance of using UAVs for the persistent collection of sensor readings from the sensor nodes located in an environment and their delivery to base stations where further processing is performed. We propose a persistent path planning and UAV allocation model, where a team of heterogeneous UAVs coming from various base stations are used to collect data from ground sensors and deliver the collected information to their closest base stations. This problem is mathematically formalised as a real-time constrained optimisation model, and proven to be NP-hard. The paper proposes a heuristic solution to the problem and evaluates its relative efficiency through performing experiments on both artificial and real sensors networks, using various scenarios of UAVs settings. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAV) and IoT)
Show Figures

Figure 1

2 pages, 149 KiB  
Editorial
Emerging Trends and Challenges in Fog and Edge Computing for the Internet of Things
by Bastien Confais and Benoît Parrein
IoT 2022, 3(1), 145-146; https://doi.org/10.3390/iot3010009 - 16 Feb 2022
Cited by 1 | Viewed by 3396
Abstract
Current network architectures such as Cloud computing are not adapted to provide an acceptable Quality of Service (QoS) to the large number of tiny devices that compose the Internet of Things (IoT) [...] Full article
22 pages, 1035 KiB  
Article
Assessing Feature Representations for Instance-Based Cross-Domain Anomaly Detection in Cloud Services Univariate Time Series Data
by Rahul Agrahari, Matthew Nicholson, Clare Conran, Haytham Assem and John D. Kelleher
IoT 2022, 3(1), 123-144; https://doi.org/10.3390/iot3010008 - 29 Jan 2022
Cited by 5 | Viewed by 4366
Abstract
In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly detection in a time series, we calculate and compare [...] Read more.
In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly detection in a time series, we calculate and compare confidence intervals on the average performance of different feature sets across a number of different model types and cross-domain time-series datasets. Our results indicate that the catch22 time-series feature set augmented with features based on rolling mean and variance performs best on average, and that the difference in performance between this feature set and the next best feature set is statistically significant. Furthermore, our analysis of the features used by the most successful model indicates that features related to mean and variance are the most informative for anomaly detection. We also find that features based on model forecast errors are useful for anomaly detection for some but not all datasets. Full article
Show Figures

Figure 1

1 pages, 123 KiB  
Editorial
Acknowledgment to Reviewers of IoT in 2021
by IoT Editorial Office
IoT 2022, 3(1), 122; https://doi.org/10.3390/iot3010007 - 28 Jan 2022
Cited by 1 | Viewed by 2705
Abstract
Rigorous peer-reviews are the basis of high-quality academic publishing [...] Full article
13 pages, 2820 KiB  
Article
Will the Internet of Things Be Perovskite Powered? Energy Yield Measurement and Real-World Performance of Perovskite Solar Cells in Ambient Light Conditions
by Suzanne K. Thomas, Adam Pockett, Krishna Seunarine, Michael Spence, Dimitrios Raptis, Simone Meroni, Trystan Watson, Matt Jones and Matthew J. Carnie
IoT 2022, 3(1), 109-121; https://doi.org/10.3390/iot3010006 - 18 Jan 2022
Cited by 7 | Viewed by 4853
Abstract
The number of interconnected devices, often referred to as the Internet of Things (IoT), is increasing at a considerable rate. It is inevitable therefore that so too will the energy demand. IoT describes a range of technologies such as sensors, software, smart meters, [...] Read more.
The number of interconnected devices, often referred to as the Internet of Things (IoT), is increasing at a considerable rate. It is inevitable therefore that so too will the energy demand. IoT describes a range of technologies such as sensors, software, smart meters, wearable devices, and communication beacons for the purpose of connecting and exchanging data with other devices and systems over the internet. Often not located near a mains supply power source, these devices may be reliant on primary battery cells. To avoid the need to periodically replace these batteries, it makes sense to integrate the technologies with a photovoltaic (PV) cell to harvest ambient light, so that the technologies can be said to be self-powered. Perovskite solar cells have proven extremely efficient in low-light conditions but in the absence of ambient and low-light testing standards, or even a consensus on what is defined by “ambient light”, it is difficult to estimate the energy yield of a given PV technology in a given scenario. Ambient light harvesting is complex, subject to spectral considerations, and whether the light source is directly incident on the PV cell. Here, we present a realistic scenario-driven method for measuring the energy yield for a given PV technology in various situations in which an IoT device may be found. Furthermore, we show that laboratory-built p-i-n perovskite devices, for many scenarios, produce energy yields close to that of commercial GaAs solar cells. Finally, we demonstrate an IoT device, powered by a mesoporous carbon perovskite solar module and supercapacitor, and operating through several day–night cycles. Full article
Show Figures

Figure 1

18 pages, 851 KiB  
Article
Context Diffusion in Fog Colonies: Exploring Autonomous Fog Node Operation Using ECTORAS
by Vasileios Nikolopoulos, Mara Nikolaidou, Maria Voreakou and Dimosthenis Anagnostopoulos
IoT 2022, 3(1), 91-108; https://doi.org/10.3390/iot3010005 - 18 Jan 2022
Cited by 2 | Viewed by 3486
Abstract
In Fog Computing, fog colonies are formed by nodes cooperating to provide services to end-users. To enable efficient operation and seamless scalability of fog colonies, decentralized control over participating nodes should be promoted. In such cases, autonomous Fog Nodes operate independently, sharing the [...] Read more.
In Fog Computing, fog colonies are formed by nodes cooperating to provide services to end-users. To enable efficient operation and seamless scalability of fog colonies, decentralized control over participating nodes should be promoted. In such cases, autonomous Fog Nodes operate independently, sharing the context in which all colony members provide their services. In the paper, we explore different techniques of context diffusion and knowledge sharing between autonomous Fog Nodes within a fog colony, using ECTORAS, a publish/subscribe protocol. With ECTORAS, nodes become actively aware of their operating context, share contextual information and exchange operational policies to achieve self-configuration, self-adaptation and context awareness in an intelligent manner. Two different ECTORAS implementations are studied, one offering centralized control with the existence of a message broker, to manage colony participants and available topics, and one fully decentralized, catering to the erratic topology that Fog Computing may produce. The two schemes are tested as the Fog Colony size is expanding in terms of performance and energy consumption, in a prototype implementation based on Raspberry Pi nodes for smart building management. Full article
Show Figures

Figure 1

18 pages, 8694 KiB  
Article
IoTivity Cloud-Enabled Platform for Energy Management Applications
by Yann Stephen Mandza and Atanda Raji
IoT 2022, 3(1), 73-90; https://doi.org/10.3390/iot3010004 - 27 Dec 2021
Cited by 6 | Viewed by 4860
Abstract
In developing countries today, population growth and the penetration of higher standard of living appliances in homes has resulted in a rapidly increasing residential load. In South Africa, the recent rolling blackouts and electricity price increase only highlighted this reality, calling for sustainable [...] Read more.
In developing countries today, population growth and the penetration of higher standard of living appliances in homes has resulted in a rapidly increasing residential load. In South Africa, the recent rolling blackouts and electricity price increase only highlighted this reality, calling for sustainable measures to reduce overall consumption and peak load. The dawn of the smart grid concept, embedded systems, and ICTs have paved the way for novel Home Energy Management Systems (HEMS) design. In this regard, the Internet of Things (IoT), an enabler for intelligent and efficient energy management systems, is the subject of increasing attention for optimizing HEMS design and mitigating its deployment cost constraints. In this work, we propose an IoT platform for residential energy management applications focusing on interoperability, low cost, technology availability, and scalability. We addressed the backend complexities of IoT Home Area Networks (HAN) using the Open Consortium Foundation (OCF) IoTivity-Lite middleware. To augment the quality, servicing, reduce the cost, and the development complexities, this work leverages open-source cloud technologies from Back4App as Backend-as-a-Service (BaaS) to provide consumers and utilities with a data communication platform within an experimental study illustrating time and space agnostic “mind-changing” energy feedback, Demand Response Management (DRM) under a peak shaving algorithm yielded peak load reduction around 15% of the based load, and appliance operation control using a HEM App via an Android smartphone. Full article
Show Figures

Figure 1

13 pages, 3272 KiB  
Article
A MODWT-Based Algorithm for the Identification and Removal of Jumps/Short-Term Distortions in Displacement Measurements Used for Structural Health Monitoring
by Davi V. Q. Rodrigues, Delong Zuo and Changzhi Li
IoT 2022, 3(1), 60-72; https://doi.org/10.3390/iot3010003 - 24 Dec 2021
Cited by 4 | Viewed by 3667
Abstract
Researchers have made substantial efforts to improve the measurement of structural reciprocal motion using radars in the last years. However, the signal-to-noise ratio of the radar’s received signal still plays an important role for long-term monitoring of structures that are susceptible to excessive [...] Read more.
Researchers have made substantial efforts to improve the measurement of structural reciprocal motion using radars in the last years. However, the signal-to-noise ratio of the radar’s received signal still plays an important role for long-term monitoring of structures that are susceptible to excessive vibration. Although the prolonged monitoring of structural deflections may provide paramount information for the assessment of structural condition, most of the existing structural health monitoring (SHM) works did not consider the challenges to handle long-term displacement measurements when the signal-to-noise ratio of the measurement is low. This may cause discontinuities in the detected reciprocal motion and can result in wrong assessments during the data analyses. This paper introduces a novel approach that uses a wavelet-based multi-resolution analysis to correct short-term distortions in the calculated displacements even when previously proposed denoising techniques are not effective. Experimental results are presented to validate and demonstrate the feasibility of the proposed algorithm. The advantages and limitations of the proposed approach are also discussed. Full article
Show Figures

Figure 1

31 pages, 1423 KiB  
Article
Big Data and Energy Security: Impacts on Private Companies, National Economies and Societies
by Hossein Hassani, Nadejda Komendantova, Daniel Kroos, Stephan Unger and Mohammad Reza Yeganegi
IoT 2022, 3(1), 29-59; https://doi.org/10.3390/iot3010002 - 23 Dec 2021
Cited by 4 | Viewed by 4127
Abstract
The importance of energy security for the successful functioning of private companies, national economies, and the overall society cannot be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the [...] Read more.
The importance of energy security for the successful functioning of private companies, national economies, and the overall society cannot be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the well-being of everybody. Uncertainty in terms of the availability of information, namely reliable data to make predictions and to plan for investment as well as for other actions of stakeholders in the energy markets is one of the factors with the highest influence on energy security. This uncertainty can be connected with many factors, such as the availability of reliable data or actions of stakeholders themselves. For example, the recent outbreak of the COVID-19 pandemic revealed negative impacts of uncertainty on decision-making processes and markets. At the time point when the market participants started to receive real-time information about the situation, the energy markets began to ease. This is one scenario where Big Data can be used to amplify information to various stakeholders to prevent panic and to ensure market stability and security of supply. Considering the novelty of this topic, our methodology is based on the meta-analysis of existing studies in the area of impacts of energy security on private companies, the national economy, and society. The results show that, in a fast-paced digital world characterized by technological advances, the use of Big Data technology provides a unique niche point to close this gap in information disparity by levering the use of unconventional data sources to integrate technologies, stakeholders, and markets to promote energy security and market stability. The potential of Big Data technology is yet to be fully utilized. Big Data can handle large data sets characterized by volume, variety, velocity, value, and complexity. Our conclusion is that the challenge for energy markets is to leverage this technology to mine available socioeconomic, political, geographic, and environmental data responsibly and to provide indicators that predict future global supply and demand. This information is crucial for energy security and ensuring global economic prosperity. Full article
(This article belongs to the Special Issue Artificial Intelligence and IoNT for Multi-Disciplinary Applications)
Show Figures

Figure 1

28 pages, 3417 KiB  
Article
Performance Analysis of Secure Elements for IoT
by Mario Noseda, Lea Zimmerli, Tobias Schläpfer and Andreas Rüst
IoT 2022, 3(1), 1-28; https://doi.org/10.3390/iot3010001 - 21 Dec 2021
Cited by 9 | Viewed by 6681
Abstract
New protocol stacks provide wireless IPv6 connectivity down to low power embedded IoT devices. From a security point of view, this leads to high exposure of such IoT devices. Consequently, even though they are highly resource-constrained, these IoT devices need to fulfil similar [...] Read more.
New protocol stacks provide wireless IPv6 connectivity down to low power embedded IoT devices. From a security point of view, this leads to high exposure of such IoT devices. Consequently, even though they are highly resource-constrained, these IoT devices need to fulfil similar security requirements as conventional computers. The challenge is to leverage well-known cybersecurity techniques for such devices without dramatically increasing power consumption (and therefore reducing battery lifetime) or the cost regarding memory sizes and required processor performance. Various semiconductor vendors have introduced dedicated hardware devices, so-called secure elements that address these cryptographic challenges. Secure elements provide tamper-resistant memory and hardware-accelerated cryptographic computation support. Moreover, they can be used for mutual authentication with peers, ensuring data integrity and confidentiality, and various other security-related use cases. Nevertheless, publicly available performance figures on energy consumption and execution times are scarce. This paper introduces the concept of secure elements and provides a measurement setup for selected individual cryptographic primitives and a Datagram Transport Layer Security (DTLS) handshake over secure Constrained Application Protocol (CoAPs) in a realistic use case. Consequently, the paper presents quantitative results for the performance of five secure elements. Based on these results, we discuss the characteristics of the individual secure elements and supply developers with the information needed to select a suitable secure element for a specific application. Full article
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop