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Recent Trends and Advances in Wireless Sensor Networks and the Internet of Things

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 20 May 2025 | Viewed by 1681

Special Issue Editors

Prof. Dr. Dionisis Kandris

E-Mail Website
Guest Editor
Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Interests: automatic control and automation methodologies and systems; algorithmic study of wireless sensor networks in terms of energy efficiency, congestion avoidance, coverage maximization, and multiobjective optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Eleftherios Anastasiadis

E-Mail Website
Guest Editor
Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Interests: algorithm design; approximation algorithms; algorithmic mechanism design; game theory, optimization algorithms for wireless sensor networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ability of Wireless Sensor Networks (WSNs) along with the Internet of Things (IoT) to support a practically endless variety of human activities places both of them among the most rapidly developing domains of Technology with a continuously growing range of applications.

On the other hand, their utilization is obstructed because of not only the limited resources of sensor nodes in terms of energy supply, memory and processing, but also the inborn restrictions of wireless communications, regarding power, speed, and capacity of communication channels and their vulnerability to interferences and intrusion. Thus, numerous challenges arise. At the same time, emerging advances in various sectors of Science and Technology seem to be promising to support and enhance the operation of WSNs and IoT, thus triggering corresponding research trends.

The aim of this Special Issue is to house research works related with the state of the art, standards, experimentations, implementations, applications, new research proposals, and case studies regarding WSNs and IoT. Invited papers have to be original and neither published nor under review in any other conference or journal. Potential topics of this special issue include, but are not limited to, the following:

  • Energy Sustainability in WSNs and IoT;
  • Energy harvesting/Energy transfer methods in WSNs and IoT;
  • Energy-efficient routing protocols;
  • Data analytics in WSNs and IoT;
  • Artificial Intelligence/Computational Intelligence for WSNs and IoT;
  • Cloud computing, edge computing, and fog computing for WSNs and IoT;
  • Sensing technologies and systems for wearables and implants;
  • WSNs and IoT in Industry 4.0;
  • 5G communication networks and mobile networks for WSN and IoT;
  • Optimization algorithms for WSNs and IoT.

Prof. Dr. Dionisis Kandris
Dr. Eleftherios Anastasiadis
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • Wireless Sensor Networks
  • Internet of Things
  • communication networks

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Published Papers (2 papers)

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Research

23 pages, 17187 KiB  
Article
Human Daily Breathing Monitoring via Analysis of CSI Ratio Trajectories for WiFi Link Pairs on the I/Q Plane
by Wei Zhuang, Yuhang Lu, Yixian Shen and Jian Su
Sensors 2024, 24(22), 7352; https://doi.org/10.3390/s24227352 - 18 Nov 2024
Viewed by 390
Abstract
The measurement of human breathing is crucial for assessing the condition of the body. It opens up possibilities for various intelligent applications, like advanced medical monitoring and sleep analysis. Conventional approaches relying on wearable devices tend to be expensive and inconvenient for users. [...] Read more.
The measurement of human breathing is crucial for assessing the condition of the body. It opens up possibilities for various intelligent applications, like advanced medical monitoring and sleep analysis. Conventional approaches relying on wearable devices tend to be expensive and inconvenient for users. Recent research has shown that inexpensive WiFi devices commonly available in the market can be utilized effectively for non-contact breathing monitoring. WiFi-based breathing monitoring is highly sensitive to motion during the breathing process. This sensitivity arises because current methods primarily rely on extracting breathing signals from the amplitude and phase variations of WiFi Channel State Information (CSI) during breathing. However, these variations can be masked by body movements, leading to inaccurate counting of breathing cycles. To address this issue, we propose a method for extracting breathing signals based on the trajectories of two-chain CSI ratios on the I/Q plane. This method accurately monitors breathing by tracking and identifying the inflection points of the CSI ratio samples’ trajectories on the I/Q plane throughout the breathing cycle. We propose a dispersion model to label and filter out CSI ratio samples representing significant motion interference, thereby enhancing the robustness of the breathing monitoring system. Furthermore, to obtain accurate breathing waveforms, we propose a method for fitting the trajectory curve of the CSI ratio samples. Based on the fitted curve, a breathing segment extraction algorithm is introduced, enabling precise breathing monitoring. Our experimental results demonstrate that this approach achieves minimal error and significantly enhances the accuracy of WiFi-based breathing monitoring. Full article
(This article belongs to the Special Issue Recent Trends and Advances in Wireless Sensor Networks and the Internet of Things)
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18 pages, 7815 KiB  
Article
An ADPLL-Based GFSK Modulator with Two-Point Modulation for IoT Applications
by Nam-Seog Kim
Sensors 2024, 24(16), 5255; https://doi.org/10.3390/s24165255 - 14 Aug 2024
Viewed by 843
Abstract
To establish ubiquitous and energy-efficient wireless sensor networks (WSNs), short-range Internet of Things (IoT) devices require Bluetooth low energy (BLE) technology, which functions at 2.4 GHz. This study presents a novel approach as follows: a fully integrated all-digital phase-locked loop (ADPLL)-based Gaussian frequency [...] Read more.
To establish ubiquitous and energy-efficient wireless sensor networks (WSNs), short-range Internet of Things (IoT) devices require Bluetooth low energy (BLE) technology, which functions at 2.4 GHz. This study presents a novel approach as follows: a fully integrated all-digital phase-locked loop (ADPLL)-based Gaussian frequency shift keying (GFSK) modulator incorporating two-point modulation (TPM). The modulator aims to enhance the efficiency of BLE communication in these networks. The design includes a time-to-digital converter (TDC) with the following three key features to improve linearity and time resolution: fast settling time, low dropout regulators (LDOs) that adapt to process, voltage, and temperature (PVT) variations, and interpolation assisted by an analog-to-digital converter (ADC). It features a digital controlled oscillator (DCO) with two key enhancements as follows: ΔΣ modulator dithering and hierarchical capacitive banks, which expand the frequency tuning range and improve linearity, and an integrated, fast-converging least-mean-square (LMS) algorithm for DCO gain calibration, which ensures compliance with BLE 5.0 stable modulation index (SMI) requirements. Implemented in a 28 nm CMOS process, occupying an active area of 0.33 mm2, the modulator demonstrates a wide frequency tuning range of from 2.21 to 2.58 GHz, in-band phase noise of −102.1 dBc/Hz, and FSK error of 1.42% while consuming 1.6 mW. Full article
(This article belongs to the Special Issue Recent Trends and Advances in Wireless Sensor Networks and the Internet of Things)
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