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IoT Sensors Development and Application for Environment & Safety
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IoT Sensors Development and Application for Environment & Safety

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

Deadline for manuscript submissions: 20 February 2025 | Viewed by 8207

Special Issue Editors

Dr. Andrea Ria

E-Mail Website
Guest Editor
IEIIT - National Research Council (CNR), Pisa, Italy
Interests: Integrated circuits; sensor interfaces; low power/voltage electronics
Dr. Massimo Piotto

E-Mail Website
Guest Editor
Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
Interests: MEMS sensors; multiphysics simulations; integrated thermal sensors; CMOS-MEMS technologies; electronics for sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, the growing interest in the potential use of smart sensors has stimulated research in this field. Many governments offer funding for research into the development of innovative devices for controlling airborne pollutants, but also for controlling classical parameters such as temperature and humidity. These controls are all the more important in the workplace where people’s health must be preserved. Wearable devices play a key role. The results of these controls can be shared in even complex sensor systems, creating pervasive sensor networks in order to reduce power and area consumption.

This Special Issue, therefore, aims to put together original research and review articles on recent advances, technologies, solutions, applications, and new challenges in the field of sensing for environment and safety.

Dr. Andrea Ria
Dr. Massimo Piotto
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

  • sensors
  • integrated sensor/interfaces
  • IoT sensor system
  • wireless sensing
  • environmental sensing
  • smart sensing for safety
  • wearable sensors

Published Papers (3 papers)

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Research

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20 pages, 10183 KiB  
Article
Federated Learning via Augmented Knowledge Distillation for Heterogenous Deep Human Activity Recognition Systems
by Gad Gad and Zubair Fadlullah
Sensors 2023, 23(1), 6; https://doi.org/10.3390/s23010006 - 20 Dec 2022
Cited by 5 | Viewed by 2436
Abstract
Deep learning-based Human Activity Recognition (HAR) systems received a lot of interest for health monitoring and activity tracking on wearable devices. The availability of large and representative datasets is often a requirement for training accurate deep learning models. To keep private data on [...] Read more.
Deep learning-based Human Activity Recognition (HAR) systems received a lot of interest for health monitoring and activity tracking on wearable devices. The availability of large and representative datasets is often a requirement for training accurate deep learning models. To keep private data on users’ devices while utilizing them to train deep learning models on huge datasets, Federated Learning (FL) was introduced as an inherently private distributed training paradigm. However, standard FL (FedAvg) lacks the capability to train heterogeneous model architectures. In this paper, we propose Federated Learning via Augmented Knowledge Distillation (FedAKD) for distributed training of heterogeneous models. FedAKD is evaluated on two HAR datasets: A waist-mounted tabular HAR dataset and a wrist-mounted time-series HAR dataset. FedAKD is more flexible than standard federated learning (FedAvg) as it enables collaborative heterogeneous deep learning models with various learning capacities. In the considered FL experiments, the communication overhead under FedAKD is 200X less compared with FL methods that communicate models’ gradients/weights. Relative to other model-agnostic FL methods, results show that FedAKD boosts performance gains of clients by up to 20 percent. Furthermore, FedAKD is shown to be relatively more robust under statistical heterogeneous scenarios. Full article
(This article belongs to the Special Issue IoT Sensors Development and Application for Environment & Safety)
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Review

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15 pages, 2181 KiB  
Review
PT-Symmetric LC Passive Wireless Sensing
by Dong-Yan Chen, Lei Dong and Qing-An Huang
Sensors 2023, 23(11), 5191; https://doi.org/10.3390/s23115191 - 30 May 2023
Cited by 1 | Viewed by 1723
Abstract
Parity–time (PT) symmetry challenges the long-held theoretical basis that only Hermitian operators correspond to observable phenomena in quantum mechanics. Non-Hermitian Hamiltonians satisfying PT symmetry also have a real-valued energy spectrum. In the field of inductor–capacitor (LC) passive wireless sensors, PT symmetry [...] Read more.
Parity–time (PT) symmetry challenges the long-held theoretical basis that only Hermitian operators correspond to observable phenomena in quantum mechanics. Non-Hermitian Hamiltonians satisfying PT symmetry also have a real-valued energy spectrum. In the field of inductor–capacitor (LC) passive wireless sensors, PT symmetry is mainly used for improving performance in terms of multi-parameter sensing, ultrahigh sensitivity, and longer interrogation distance. For example, the proposal of both higher-order PT symmetry and divergent exceptional points can utilize a more drastic bifurcation process around exceptional points (EPs) to accomplish a significantly higher sensitivity and spectral resolution. However, there are still many controversies regarding the inevitable noise and actual precision of the EP sensors. In this review, we systematically present the research status of PT-symmetric LC sensors in three working areas: exact phase, exceptional point, and broken phase, demonstrating the advantages of non-Hermitian sensing concerning classical LC sensing principles. Full article
(This article belongs to the Special Issue IoT Sensors Development and Application for Environment & Safety)
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29 pages, 4486 KiB  
Review
Recent Implementations of Hydrogel-Based Microbial Electrochemical Technologies (METs) in Sensing Applications
by Zeena Wang, Dunzhu Li, Yunhong Shi, Yifan Sun, Saviour I. Okeke, Luming Yang, Wen Zhang, Zihan Zhang, Yanqi Shi and Liwen Xiao
Sensors 2023, 23(2), 641; https://doi.org/10.3390/s23020641 - 6 Jan 2023
Cited by 5 | Viewed by 3343
Abstract
Hydrogel materials have been used extensively in microbial electrochemical technology (MET) and sensor development due to their high biocompatibility and low toxicity. With an increasing demand for sensors across different sectors, it is crucial to understand the current state within the sectors of [...] Read more.
Hydrogel materials have been used extensively in microbial electrochemical technology (MET) and sensor development due to their high biocompatibility and low toxicity. With an increasing demand for sensors across different sectors, it is crucial to understand the current state within the sectors of hydrogel METs and sensors. Surprisingly, a systematic review examining the application of hydrogel-based METs to sensor technologies has not yet been conducted. This review aimed to identify the current research progress surrounding the incorporation of hydrogels within METs and sensors development, with a specific focus on microbial fuel cells (MFCs) and microbial electrolysis cells (MECs). The manufacturing process/cost, operational performance, analysis accuracy and stability of typical hydrogel materials in METs and sensors were summarised and analysed. The current challenges facing the technology as well as potential direction for future research were also discussed. This review will substantially promote the understanding of hydrogel materials used in METs and benefit the development of electrochemical biosensors using hydrogel-based METs. Full article
(This article belongs to the Special Issue IoT Sensors Development and Application for Environment & Safety)
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