IET Wireless Sensor Systems最新文献

DFROG-MAC: A Dynamic Fragmentation-Based MAC for Prioritised Emergency Data Management in Vehicular Networks DFROG-MAC：一种基于动态分片的车辆网络应急数据优先管理MAC

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-10-10 DOI: 10.1049/wss2.70017

Anwar Ahmed Khan, Shama Siddiqui, Ahmad Sami Al-Shamayleh, Adnan Akhunzada, Indrakshi Dey

{"title":"DFROG-MAC: A Dynamic Fragmentation-Based MAC for Prioritised Emergency Data Management in Vehicular Networks","authors":"Anwar Ahmed Khan, Shama Siddiqui, Ahmad Sami Al-Shamayleh, Adnan Akhunzada, Indrakshi Dey","doi":"10.1049/wss2.70017","DOIUrl":"https://doi.org/10.1049/wss2.70017","url":null,"abstract":"The rapid advancements in vehicular ad hoc networks (VANETs) call for development of effective networking schemes. Managing heterogenous traffic in VANETs becomes a critical challenge, especially when dealing with critical scenarios. In this paper, we present a novel dynamic fragmentation-based MAC protocol, DFROG-MAC for Internet of Things (IoT) applications in VANET environment. This protocol is focused on facilitating prioritised heterogenous traffic in sensor networks and hence, can offer a distinguished quality of service for various application areas such as vehicular, industrial or body sensor networks. DFROG-MAC deploys fragmentation scheme for low priority data, so the high priority data may interrupt and access channel without needing to wait for the complete transmission of lower priority data. The fragment size for the lower priority data is dynamically adjusted at the runtime based on the frequency of urgent traffic arrival. This dynamic approach helps to ensure that the channel does not remain idle, and lower priority traffic could be served quickly, in the absence of urgent traffic. Two types of traffic priorities, normal and urgent have been used for performance evaluation of FROG-MAC and DFROG-MAC, over Contiki platform, with the scope of this study focused on vehicle-to-infrastructure (V2I) single-hop communication. The delay and throughput both have been found to improve for DFROG-MAC due to the possibility of dynamic fragment size selection.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272644","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

Multivariate Lifetime Prediction Model for Energy Efficient Region-Based Wireless Sensor Network 基于区域的高能效无线传感器网络多变量寿命预测模型

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-08-17 DOI: 10.1049/wss2.70015

Vipul Narayan, Swapnita Srivastava, Vikash Kumar Mishra, Mohammad Faiz, Shilpi Sharma, Vipin Balyan, Gunjan Gupta

{"title":"Multivariate Lifetime Prediction Model for Energy Efficient Region-Based Wireless Sensor Network","authors":"Vipul Narayan, Swapnita Srivastava, Vikash Kumar Mishra, Mohammad Faiz, Shilpi Sharma, Vipin Balyan, Gunjan Gupta","doi":"10.1049/wss2.70015","DOIUrl":"10.1049/wss2.70015","url":null,"abstract":"In wireless sensor networks (WSNs), optimising energy efficiency while maintaining coverage and managing resource constraints remains a critical challenge. This paper introduces a novel Region-Based Multilevel Energy Efficiency Protocol (RBMEEP), which innovatively partitions the network into regions and sub-regions to enhance energy utilisation through optimised clustering and communication with the base station (BS). Unlike conventional protocols, RBMEEP significantly extends network lifetime, outperforming the Stable Election Protocol (SEP). The novelty lies in the integration of a Regression Prediction Model (RPM), which accurately predicts network lifetime based on node density and packet size. Simulation results demonstrate the model's high prediction accuracy, with up to 99.94% in smaller network areas and 99.87% in larger areas. This predictive capability allows for adaptable and efficient WSN design, tailored to specific user requirements. The proposed approach presents a significant advancement in extending the operational life of WSNs, offering a robust solution for energy and coverage optimisation. This work not only improves the theoretical understanding of WSN energy efficiency but also provides a practical framework that can be deployed in real-world scenarios.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144861719","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

Optimising Internet of Things (IoT) Performance Through Cloud, Fog and Edge Computing Architecture 通过云、雾和边缘计算架构优化物联网（IoT）性能

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-08-15 DOI: 10.1049/wss2.70016

Shams Forruque Ahmed, Shanjana Shuravi Shawon, Shaila Afrin, Sabiha Jannat Rafa, Mahfara Hoque, Amir H. Gandomi

{"title":"Optimising Internet of Things (IoT) Performance Through Cloud, Fog and Edge Computing Architecture","authors":"Shams Forruque Ahmed, Shanjana Shuravi Shawon, Shaila Afrin, Sabiha Jannat Rafa, Mahfara Hoque, Amir H. Gandomi","doi":"10.1049/wss2.70016","DOIUrl":"10.1049/wss2.70016","url":null,"abstract":"The Internet of Things (IoT) revolutionises communication systems and enables transformative applications across diverse domains. However, existing reviews often focus on integrating IoT with only one or two computing paradigms—cloud, fog, or edge computing—overlooking the holistic synergy of these architectures. This review bridges that gap by providing a comprehensive analysis of IoT integration with all three paradigms, emphasising their collective potential to address the challenges of scalability, latency, and computational efficiency. The findings highlight that cloud computing ensures scalable storage and processing but struggles with latency-sensitive IoT applications. Fog computing reduces latency by processing data near the network edge, achieving up to a 40% improvement in response times for real-time applications. Edge computing complements this by ensuring immediate data handling, reducing transmission delays by approximately 30% compared to cloud-centric models. Despite these advances, challenges persist, including high energy consumption, security vulnerabilities, and the complexity of managing dynamic workflows across architectures. This review provides actionable recommendations for future research, including the development of energy-efficient algorithms, robust security protocols, and adaptive frameworks for seamless integration. These directions are vital for advancing IoT as an indispensable component of the future Internet, fostering smarter and more connected systems across industries.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"15 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144853686","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

Secured Clustered Wireless Sensor Network Using Ensemble Hamming Code and Quadratic Residue and Nonresidue Properties 基于集成汉明码和二次残馀与非残馀性质的安全聚类无线传感器网络

IF 2.4

IET Wireless Sensor Systems Pub Date : 2025-07-16 DOI: 10.1049/wss2.70014

Olayinka O. Ogundile, Oluwaseyi P. Babalola, Innocent E. Davidson

{"title":"Secured Clustered Wireless Sensor Network Using Ensemble Hamming Code and Quadratic Residue and Nonresidue Properties","authors":"Olayinka O. Ogundile, Oluwaseyi P. Babalola, Innocent E. Davidson","doi":"10.1049/wss2.70014","DOIUrl":"10.1049/wss2.70014","url":null,"abstract":"Wireless sensor networks (WSNs) are increasingly used in critical sectors such as defence, healthcare and environmental monitoring. These networks rely on small resource-constrained sensor nodes that communicate wirelessly, making them vulnerable to security threats. Although cryptographic methods, time synchronisation and error-correcting codes (ECCs) offer some protection, they often struggle with the computational and energy limitations of sensor nodes. Among ECCs, Hamming codes combined with quadratic residue (H-QR) techniques have shown promise in enhancing network security and improving performance metrics such as packet delivery ratio (PDR) and throughput (TP). However, existing H-QR implementations are limited in scalability, supporting only small networks with up to 15 nodes. To address this limitation, this study introduces an enhanced security architecture for clustered WSNs using Hamming codes with quadratic residue and nonresidue (H-QRN) properties. The proposed H-QRN scheme supports an arbitrary number of sensor nodes, making it suitable for large-scale and diverse industrial applications. Simulation results demonstrate that H-QRN significantly improves PDR and TP over traditional H-QR methods while maintaining similar end-to-end delay (E2E) and control overhead (CO). This work offers a scalable and efficient security solution for WSNs and provides practical insights for selecting security protocols tailored to specific application requirements.","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/wss2.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647406","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

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