IET Wireless Sensor Systems最新文献_第5页

Internet of Things-Based Health Surveillance Systems for Livestock: A Review of Recent Advances and Challenges 基于物联网的牲畜健康监测系统：最新进展和挑战综述

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-07-16 DOI: 10.1049/wss2.70013

Mrinmoy Modak, Muin Mustahasin Pritom, Sajal Chandra Banik, Md Sanaul Rabbi

{"title":"Internet of Things-Based Health Surveillance Systems for Livestock: A Review of Recent Advances and Challenges","authors":"Mrinmoy Modak, Muin Mustahasin Pritom, Sajal Chandra Banik, Md Sanaul Rabbi","doi":"10.1049/wss2.70013","DOIUrl":"10.1049/wss2.70013","url":null,"abstract":"Livestock monitoring systems have been significantly transformed by the implementation of Internet of Things (IoT) technology in agriculture. This integration enables the collection and analysis of data in real time, which contributes to improved animal welfare and productivity. This paper showcases the integration of various microcontrollers, sensors and sophisticated algorithms to give an extensive assessment of the most recent IoT-based livestock health monitoring systems. A wide array of sensors, including accelerometers, temperature sensors, heart rate sensors and more, coupled with various microcontrollers, such as Raspberry Pi, ESP8266, Arduino and ESP32, are primarily used in monitoring systems. Internet of Things (IoT) platforms such as ThingSpeak and Blynk, as well as the development of online interfaces and mobile applications, provide extensive user input. The integration of state-of-the-art algorithms is explored in detail, including support vector machines (SVM), decision trees, artificial neural networks (ANN), YOLOv5 object detection, different machine learning algorithms, random forest classifiers and ThingSpeak IoT analytics platform. Particular attention is given to algorithms that detect various parameters, including acetone levels, cow location, hormone release, body temperature, activity level, bellowing, jaw movement, heart rate, temperature, oestrous cycle, detection and tracking, action recognition, size variations, motion deformation, heat stress, ambient temperature, sleep tracking and more. The purpose of this review article is to facilitate the adoption of Internet of Things (IoT) solutions for sustainable and effective livestock management practices by offering a thorough analysis of existing IoT technologies used in livestock monitoring.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-Bias Graphene Ring-Based THz Absorber: Wearable Optical Sensor 基于双偏置石墨烯环的太赫兹吸收器：可穿戴光学传感器

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-07-01 DOI: 10.1049/wss2.70010

Ilghar Rezaei, Toktam Aghaee

引用次数: 0

Multi-Objective Energy-Efficient Clustering Protocol for Wireless Sensor Networks: An Approach Based on Metaheuristic Algorithms 基于元启发式算法的无线传感器网络多目标节能聚类协议

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-07-01 DOI: 10.1049/wss2.70011

Mohamadhosein Behzadi, Homayun Motameni, Hosein Mohamadi, Behnam Barzegar

{"title":"Multi-Objective Energy-Efficient Clustering Protocol for Wireless Sensor Networks: An Approach Based on Metaheuristic Algorithms","authors":"Mohamadhosein Behzadi, Homayun Motameni, Hosein Mohamadi, Behnam Barzegar","doi":"10.1049/wss2.70011","DOIUrl":"10.1049/wss2.70011","url":null,"abstract":"Efficient resource management remains a critical challenge in wireless sensor networks (WSNs) due to the constrained nature of sensor nodes. This paper proposes a novel hybrid clustering protocol to address this issue, aiming to optimise energy consumption, extend network lifetime and enhance scalability. Our approach combines the improved version of binary dragonfly algorithm (IVBDA) for cluster head (CH) selection and the Mamdani fuzzy inference system for effective cluster formation. After CH selection and cluster formation, a multi-hop routing mechanism transmits data packets within the WSN. To validate the performance of the proposed protocol, extensive simulations are conducted on various network topologies, evaluating metrics such as average energy consumption, live node count, network lifetime, and packet reception at the base station (BS). Comparative analyses with existing clustering protocols and other metaheuristic algorithms, including binary particle swarm optimisation (BPSO), binary whale optimisation algorithm (BWOA) and binary dragonfly algorithm (BDA), demonstrate the superior performance of the proposed hybrid approach in terms of energy efficiency, network longevity and overall WSN performance. The improved version of BDA shows faster convergence than BPSO, BWOA and BDA, as ascertained by examining the multi-objective fitness function. This paper contributes significantly to the development of efficient clustering protocols and showcases the potential of hybrid metaheuristic and fuzzy inference techniques for optimising resource allocation in WSNs. The proposed protocol outperforms other protocols in network lifetime and overall performance, indicating its potential to be a valuable solution for resource management in WSNs. The evaluation of metaheuristic algorithms highlights the importance of considering convergence speed in optimising energy-efficient clustering.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Contactless Health Monitoring: An Overview of Video-Based Techniques Utilising Machine/Deep Learning 非接触式健康监测：利用机器/深度学习的视频技术概述

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-06-20 DOI: 10.1049/wss2.70009

Alaa Hajr, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

{"title":"Contactless Health Monitoring: An Overview of Video-Based Techniques Utilising Machine/Deep Learning","authors":"Alaa Hajr, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari","doi":"10.1049/wss2.70009","DOIUrl":"10.1049/wss2.70009","url":null,"abstract":"Vital signs are crucial indicators of an individual's physiological well-being and represent one of the primary evaluations conducted in clinical and hospital environments. A comprehensive evaluation of a patient's health state depends on these signs which include heart rate (HR), respiratory rate (RR), blood oxygen saturation (SpO2), blood pressure (BP) and body temperature (BT). In recent years, there has been significant interest in using imaging photoplethysmography (iPPG) with consumer-level cameras for contactless health monitoring (CHM) to accurately assess vital signs. The introduction of iPPG in CHM signifies the beginning of a remarkable era in the history of healthcare, whereby diagnostic processes are enhanced via the integration of technology and patient well-being. This review article presents a comprehensive examination of CHM techniques utilising machine learning (ML) and deep learning (DL) algorithms for the assessment of critical vital signs. The article addresses the challenges and research gaps identified in recent studies, particularly those related to variations in lighting conditions, head movements and the impact of different colour types on the accuracy and reliability of CHM techniques. Finally, we propose several recommendations aimed to enhance the efficiency of CHM systems. These include the development of more robust learning algorithms and the creation of diverse datasets that encompass a wide range of demographics including variations in gender, skin colour and lighting conditions.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IoT-Based Food Quality Monitoring System 基于物联网的食品质量监控系统

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-05-29 DOI: 10.1049/wss2.70008

Rashmi Tailor, Smit Parikh, Kamalakannan Kumar, Thomas Collins, Hosam El-Ocla

引用次数: 0

Distributed Gaussian Mixture PHD Filtering Under Communication Constraints 通信约束下的分布高斯混合PHD滤波

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-05-02 DOI: 10.1049/wss2.70006

Shiraz Khan, Yi-Chieh Sun, Inseok Hwang

{"title":"Distributed Gaussian Mixture PHD Filtering Under Communication Constraints","authors":"Shiraz Khan, Yi-Chieh Sun, Inseok Hwang","doi":"10.1049/wss2.70006","DOIUrl":"10.1049/wss2.70006","url":null,"abstract":"The Gaussian mixture probability hypothesis density (GM-PHD) filter is an almost exact closed-form approximation to the Bayes-optimal multi-target tracking algorithm. Due to its optimality guarantees and ease of implementation, it has been studied extensively in the literature. However, the challenges involved in implementing the GM-PHD filter efficiently in a distributed (multi-sensor) setting have received little attention. The existing solutions for distributed PHD filtering either have a high computational and communication cost, making them infeasible for wireless sensor networks with limited communication bandwidths, and/or are unable to guarantee the asymptotic convergence of the algorithm to an optimal solution. In this paper, we develop a distributed GM-PHD filtering recursion that uses a probabilistic communication rule to limit the communication bandwidth of the algorithm, while ensuring asymptotic convergence of the algorithm. The proposed algorithm uses weighted average consensus of Gaussian mixtures (GMs) to lower (and asymptotically minimise) the Cauchy–Schwarz divergences between the sensors' local estimates. In addition, the proposed probabilistic communication rule is able to avoid the issue of false positives, which has previously been noted to impact the filtering performance of distributed multi-target tracking. Through numerical simulations, it is demonstrated that our proposed method is an effective solution for distributed multi-target tracking in resource-constrained sensor networks.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Dilated CNN-Based Model for Stress Detection Using Raw PPG Signals 基于扩展cnn的原始PPG信号应力检测模型

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-04-30 DOI: 10.1049/wss2.70004

Koorosh Motaman, Khalil Alipour, Bahram Tarvirdizadeh, Mohammad Ghamari

{"title":"A Dilated CNN-Based Model for Stress Detection Using Raw PPG Signals","authors":"Koorosh Motaman, Khalil Alipour, Bahram Tarvirdizadeh, Mohammad Ghamari","doi":"10.1049/wss2.70004","DOIUrl":"10.1049/wss2.70004","url":null,"abstract":"Stress, a common response to challenging situations, has become pervasive in contemporary daily life due to various factors. Persistent stress can weaken the human immune system, increasing the risk of chronic stress and contributing to a range of physical and mental health disorders. Therefore, timely detection of stress in its early stages is crucial for preventing adverse health outcomes. Physiological signals offer insights into the body's stress-induced changes and can be leveraged for stress detection applications. Among these signals, the photoplethysmogram (PPG) signal stands out due to its advantages. This article introduces an innovative stress detection model based on dilated convolutional neural networks (Dilated CNNs), a deep learning algorithm. This model distinguishes between an individual's stressed and non-stressed states by analysing PPG signals without requiring pre-processing, denoising, or feature extraction. Leveraging the Empatica E4 PPG signals from the Wearable Stress and Affect Detection (WESAD) dataset, the authors developed and evaluated the model, achieving remarkable results: a test accuracy of 93.56% and an area under the curve (AUC) of 96.52%. These outcomes are particularly noteworthy given the streamlined data preparation process and methodological simplicity. Beyond enabling early stress diagnosis, this advancement holds promise for enhancing overall health and well-being in the fast-paced and intricate world. Additionally, its simplicity makes it suitable for real-time stress detection and integration into wearable devices.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143889072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

I-QoS-WSN-S-MDC: Improving Quality of Service of Wireless Sensor Networks Using a Smart Mobile Data Collector I-QoS-WSN-S-MDC：利用智能移动数据采集器提高无线传感器网络的服务质量

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-04-30 DOI: 10.1049/wss2.70005

Rahma Gantassi, Zaki Masood, Quota Alief Sias, Yonghoon Choi

{"title":"I-QoS-WSN-S-MDC: Improving Quality of Service of Wireless Sensor Networks Using a Smart Mobile Data Collector","authors":"Rahma Gantassi, Zaki Masood, Quota Alief Sias, Yonghoon Choi","doi":"10.1049/wss2.70005","DOIUrl":"10.1049/wss2.70005","url":null,"abstract":"Quality of service (QoS) and energy efficiency are two major factors that play an important role in wireless sensor network (WSNs) operation. Although it is often argued that these two factors are naturally consistent. WSNs demand additional QoS measures beyond the capabilities of clustering and routing protocols, such as stability and latency. This paper proposes a new routing protocol named improving quality of service of wireless sensor networks using a smart mobile data collector (I-QoS-WSN-S-MDC). I-QoS-WSN-S-MDC is an enhancement of the low energy adaptive clustering hierarchy-kmeans-grid (LEACH-K-G) and the mobile data collector-K-means (MDC-K) to find the optimal path taken by the MDC for QoS efficiency. Specifically, the proposed I-QoS-WSN-S-MDC protocol uses the K-means algorithm and the grid clustering algorithm to reduce energy consumption in the cluster head (CH) election stage. In addition, the MDC is used as an interface between the CH and the base station (BS) to improve the WSN QoS and transmission phase of the MDC-K and LEACH-G-K protocols using lin–kernighan–helsgaun-travelling salesman problem (LKH-TSP). The experimental results show that I-QoS-WSN-S-MDC outperforms several low energy adaptive clustering (LEACH) protocol enhancements such as threshold-sensitive energy efficient network (TEEN), LEACH-K, LEACH-C, Improved-LEACH, Stable-Improved-LEACH, MDC maximum distance leach, MDC minimum distance leach, MDC-K, and MDC-TSP-LEACH-K.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effective Quantised CSI-Fingerprint for DL-Based Indoor Localisation 基于dl的室内定位的有效量化csi指纹

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-04-08 DOI: 10.1049/wss2.70003

Seiha Homma, Yuta Ida, Yasuaki Ohira, Sho Kuroda, Takahiro Matsumoto

引用次数: 0

Highly Effective PCF Sensor for Ensuring Edible Oil Safety and Quality Within the THz Regime 在太赫兹范围内确保食用油安全和质量的高效PCF传感器

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-03-17 DOI: 10.1049/wss2.70002

Diponkar Kundu, Mir Sabbir Hossain, Most. Momtahina Bani, A. H. M. Iftekharul Ferdous, Khalid Sifulla Noor, Laxmi rani, Md. Safiul Islam

{"title":"Highly Effective PCF Sensor for Ensuring Edible Oil Safety and Quality Within the THz Regime","authors":"Diponkar Kundu, Mir Sabbir Hossain, Most. Momtahina Bani, A. H. M. Iftekharul Ferdous, Khalid Sifulla Noor, Laxmi rani, Md. Safiul Islam","doi":"10.1049/wss2.70002","DOIUrl":"10.1049/wss2.70002","url":null,"abstract":"This research presents a novel square hollow-core photonic crystal fibre (PCF) sensor designed for the detection of food-grade oils in the terahertz (THz) frequency range. The sensor’s effectiveness is quantitatively evaluated using COMSOL Multiphysics, a sophisticated simulation tool that employs finite element methodology (FEM) to model complex interactions within the fibre structure. Simulation outcomes reveal that, under optimal geometric parameters, the proposed sensor achieves an exceptional relative sensitivity of 98.27% for various edible oils at an ideal frequency of 2.2 THz, significantly outperforming existing technologies. Additionally, the sensor exhibits minimal confinement loss of 1.428 × 10−8 dB/m and a low effective material loss of 0.004246 cm−1, facilitating accurate detection of slight refractive index variations related to the chemical compositions of different oils. This high sensitivity enables non-destructive testing, allowing for the analysis of oils without compromising their composition or quality, thereby maintaining the integrity of food products. Ultimately, the proposed PCF sensor enhances food safety monitoring and paves the way for advanced applications in the food industry, ensuring consumers receive high-quality products.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0