Reviews and Advances in Internet of Things Technologies

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".

Deadline for manuscript submissions: closed (15 November 2021) | Viewed by 48873

Special Issue Editors

Information Engineering Department, University of Pisa and Research Center "E. Piaggio” Largo L. Lazzarino 1, 56122 Pisa, Italy
Interests: biomedical engineering; sensing technologies; soft sensors; motion capture; data fusion; biomechanics; rehabilitation; wearable sensors and technologies
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School of Electrical and Electronic Engineering Nanyang Technological University Block S1, Nanyang Avenue, Singapore 639798, Singapore
Interests: machine learning; data mining; optimization; computational intelligence
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1. Computer Science and Computer Engineering, University of Arkansas, JBHT 515, Fayetteville, AR 72701, USA
2. Faculty 1 - Mathematics, Natural and Computer Sciences, Walther-Pauer-Strasse 2, 03046 Cottbus, Germany
Interests: system on chip design; embedded systems; computer architecture; reconfigurable computing; operating system (advances and real-time); cybersecurity; adaptive systems; distributed smart cameras
Information Engineering Department, University of Pisa, Via Caruso 16, 56122 Pisa, Italy
Interests: metamaterials; chipless RFID and sensors; characteristic modes; antenna design; optimization algorithms
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DIEE - University of Cagliari, Piazza d’Armi, 09123 Cagliari, Italy
Interests: organic electronics; organic field effect transistor (OFET); organic electrochemical transistor (OECT); nonvolatile memory elements; biochemical sensors; wearable electronics; artificial skin
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Sensor Technology Research Centre, School of Engineering and Informatics, University of Sussex, Brighton BN1 9QT, UK
Interests: development, fabrication, and characterization of deformable thin-film devices on plastic substrates; innovative fabrication processes and flexible analog sensor systems
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Special Issue Information

Dear Colleagues

The Internet of Things is made of devices and objects, e.g. sensors, wearables, smartphones, that are connected together through the internet. The connected devices can be combined with automated systems and artificial intelligence to perform actions or to learn specific data patterns.

IoT technologies will revolutionise our life in the years to come. From smart objects to connected machines in factories that have the potential to enable the Industry 4.0 revolution.

This Special Issue will bring together review papers on the recent advances in the multidisciplinary field of IoT technologies and the important gaps that still remain in order to obtain massive diffusion. Articles in this Special Issue will address topics that include communication, networking, sensing, materials, integration and data science.

The Special Issue is edited by the board members of the ICT section of Technologies:

https://www.mdpi.com/journal/technologies/sectioneditors/ICT

Mailing list for the ICT community: https://lists.mdpi.com/mailman/listinfo/ict

Prof. Dr. Alessandro Tognetti
Prof. Dr. Lipo Wang
Prof. Dr. Christophe Bobda
Dr. Simone Genovesi
Dr. Piero Cosseddu
Dr. Niko Stephan Münzenrieder
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Technologies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart sensors 
  • networking 
  • flexible/stretchable electronics 
  • wearables 
  • smart textiles and smart materials 
  • cloud and fog computing 
  • low power circuits 
  • cybersecurity 
  • machine learning
  • RFID

Published Papers (5 papers)

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Research

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11 pages, 1697 KiB  
Article
Radiation Efficiency Enhancement of Graphene Plasmonic Devices Using Matching Circuits
by Stamatios Amanatiadis, Theodoros Zygiridis and Nikolaos Kantartzis
Technologies 2021, 9(1), 4; https://doi.org/10.3390/technologies9010004 - 02 Jan 2021
Cited by 1 | Viewed by 2151
Abstract
In the present work, the radiation properties of a graphene plasmonic patch antenna are investigated and enhanced in terms of efficiency, utilizing circuit-matching techniques. Initially, the reflection coefficient of graphene surface waves due to discontinuities is studied, while the power flow towards free-space [...] Read more.
In the present work, the radiation properties of a graphene plasmonic patch antenna are investigated and enhanced in terms of efficiency, utilizing circuit-matching techniques. Initially, the reflection coefficient of graphene surface waves due to discontinuities is studied, while the power flow towards free-space is numerically extracted. This analysis indicates that the radiated power is increased for higher values of the chemical potential, although the surface wave is weakly confined and prone to degradation due to interference. For this reason, a graphene sheet that supports strongly confined surface waves is terminated via a matching layer, in order to enhance the radiating power. In particular, the matching layer consists of an appropriately selected larger chemical potential value, in order to minimize the reflection coefficient and boost the radiation performance. The numerical investigation of this setup validates the upgraded performance, since the radiating power is significantly increased. Then, a realistic setup that includes a graphene patch antenna is examined numerically, proving the augmentation of the radiation efficiency when the matching layer is utilized. Finally, the latter is designed with a graded increment in the chemical potential, and the computational analysis highlights the significant enhancement of the graphene plasmonic antenna gain towards the desired direction. Consequently, a more reliable framework for wireless communications between plasmonic devices at THz frequencies is established, which corresponds to the practical significance of the proposed methodology for improved radiation efficiency. All numerical results are extracted by means of an efficient modification of the Finite-Difference Time-Domain (FDTD) scheme, which models graphene accurately. Full article
(This article belongs to the Special Issue Reviews and Advances in Internet of Things Technologies)
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16 pages, 1215 KiB  
Article
A Space-Time Correlation Model for MRC Receivers in Rayleigh Fading Channels
by Ramiro Sámano-Robles
Technologies 2020, 8(3), 41; https://doi.org/10.3390/technologies8030041 - 22 Jul 2020
Cited by 1 | Viewed by 3355
Abstract
This paper presents a statistical model for maximum ratio combining (MRC) receivers in Rayleigh fading channels enabled with a temporal combining process. This means that the receiver effectively combines spatial and temporal branch components. Therefore, the signals that will be processed by the [...] Read more.
This paper presents a statistical model for maximum ratio combining (MRC) receivers in Rayleigh fading channels enabled with a temporal combining process. This means that the receiver effectively combines spatial and temporal branch components. Therefore, the signals that will be processed by the MRC receiver are collected not only across different antennas (space), but also at different instants of time. This suggests the use of a retransmission, repetition or space-time coding algorithm that forces the receiver to store signals in memory at different instants of time. Eventually, these stored signals are combined after a predefined or dynamically optimized number of time-slots or retransmissions. The model includes temporal correlation features in addition to the space correlation between the signals of the different components or branches of the MRC receiver. The derivation uses a frequency domain approach (using the characteristic function of the random variables) to obtain closed-form expressions of the statistics of the post-processing signal-to-noise ratio (SNR) under the assumption of equivalent correlation in time and equivalent correlation in space. The described methodology paves the way for the reformulation of other statistical functions as a frequency-domain polynomial root analysis problem. This is opposed to the infinite series approach that is used in the conventional methodology using directly the probability density function (PDF). The results suggest that temporal diversity is a good complement to receivers with limited spatial diversity capabilities. It is also shown that this additional operation could be maximized when the temporal diversity is adaptive (i.e., activated by thresholds of SNR), thus leading to a better resource utilization. Full article
(This article belongs to the Special Issue Reviews and Advances in Internet of Things Technologies)
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14 pages, 1592 KiB  
Article
Evaluation of Epidemic-Based Information Dissemination in a Wireless Network Testbed
by Andreana Stylidou, Alexandros Zervopoulos, Aikaterini Georgia Alvanou, George Koufoudakis, Georgios Tsoumanis and Konstantinos Oikonomou
Technologies 2020, 8(3), 36; https://doi.org/10.3390/technologies8030036 - 28 Jun 2020
Cited by 2 | Viewed by 3181
Abstract
Information dissemination is an integral part of modern networking environments, such as Wireless Sensor Networks (WSNs). Probabilistic flooding, a common epidemic-based approach, is used as an efficient alternative to traditional blind flooding as it minimizes redundant transmissions and energy consumption. It shares some [...] Read more.
Information dissemination is an integral part of modern networking environments, such as Wireless Sensor Networks (WSNs). Probabilistic flooding, a common epidemic-based approach, is used as an efficient alternative to traditional blind flooding as it minimizes redundant transmissions and energy consumption. It shares some similarities with the Susceptible-Infected-Recovered (SIR) epidemic model, in the sense that the dissemination process and the epidemic thresholds, which achieve maximum coverage with the minimum required transmissions, have been found to be common in certain cases. In this paper, some of these similarities between probabilistic flooding and the SIR epidemic model are identified, particularly with respect to the epidemic thresholds. Both of these epidemic algorithms are experimentally evaluated on a university campus testbed, where a low-cost WSN, consisting of 25 nodes, is deployed. Both algorithm implementations are shown to be efficient at covering a large portion of the network’s nodes, with probabilistic flooding behaving largely in accordance with the considered epidemic thresholds. On the other hand, the implementation of the SIR epidemic model behaves quite unexpectedly, as the epidemic thresholds underestimate sufficient network coverage, a fact that can be attributed to implementation limitations. Full article
(This article belongs to the Special Issue Reviews and Advances in Internet of Things Technologies)
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Review

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52 pages, 1257 KiB  
Review
Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey
by Eljona Zanaj, Giuseppe Caso, Luca De Nardis, Alireza Mohammadpour, Özgü Alay and Maria-Gabriella Di Benedetto
Technologies 2021, 9(1), 22; https://doi.org/10.3390/technologies9010022 - 19 Mar 2021
Cited by 19 | Viewed by 6172
Abstract
In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers [...] Read more.
In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions. Full article
(This article belongs to the Special Issue Reviews and Advances in Internet of Things Technologies)
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81 pages, 49064 KiB  
Review
Flexible Sensors—From Materials to Applications
by Júlio C. Costa, Filippo Spina, Pasindu Lugoda, Leonardo Garcia-Garcia, Daniel Roggen and Niko Münzenrieder
Technologies 2019, 7(2), 35; https://doi.org/10.3390/technologies7020035 - 09 Apr 2019
Cited by 140 | Viewed by 32565
Abstract
Flexible sensors have the potential to be seamlessly applied to soft and irregularly shaped surfaces such as the human skin or textile fabrics. This benefits conformability dependant applications including smart tattoos, artificial skins and soft robotics. Consequently, materials and structures for innovative flexible [...] Read more.
Flexible sensors have the potential to be seamlessly applied to soft and irregularly shaped surfaces such as the human skin or textile fabrics. This benefits conformability dependant applications including smart tattoos, artificial skins and soft robotics. Consequently, materials and structures for innovative flexible sensors, as well as their integration into systems, continue to be in the spotlight of research. This review outlines the current state of flexible sensor technologies and the impact of material developments on this field. Special attention is given to strain, temperature, chemical, light and electropotential sensors, as well as their respective applications. Full article
(This article belongs to the Special Issue Reviews and Advances in Internet of Things Technologies)
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