IET Wireless Sensor Systems最新文献_第2页

Smart Agriculture Through Internet of Things and Machine Learning: A Survey of Monitoring Techniques, Methods and Applications 基于物联网和机器学习的智慧农业：监测技术、方法和应用综述

IF 2.5

IET Wireless Sensor Systems Pub Date : 2026-07-03 DOI: 10.1049/wss2.70033

Ado Adamou Abba Ari, Emmanuel Baba, Hamayadji Abdoul Aziz, Khouloud Boukadi, Ousmane Thiare, Abdelhak Mourad Gueroui

{"title":"Smart Agriculture Through Internet of Things and Machine Learning: A Survey of Monitoring Techniques, Methods and Applications","authors":"Ado Adamou Abba Ari, Emmanuel Baba, Hamayadji Abdoul Aziz, Khouloud Boukadi, Ousmane Thiare, Abdelhak Mourad Gueroui","doi":"10.1049/wss2.70033","DOIUrl":"10.1049/wss2.70033","url":null,"abstract":"In today's digital era, the rapid proliferation of connected devices and the growing impact of artificial intelligence (AI) have created a powerful synergy, reshaping multiple sectors, including agriculture. This convergence has led to the rise of smart farming systems, where the Internet of things (IoT) enables large-scale continuous data collection from diverse agricultural environments, whereas machine learning (ML) provides the analytical capacity to process, interpret and transform these data into actionable insights. Together, IoT and ML empower farmers and stakeholders to make informed timely decisions that improve efficiency, productivity and sustainability. This article explores the integration of IoT and ML in agricultural monitoring systems. It reviews major application domains, surveys data collection strategies using wireless sensors, aerial vehicles and animal monitoring systems and discusses underlying architectures, topologies and communication protocols. Furthermore, it examines ML methods applied to interpret data, optimise IoT networks and support decision-making. Special focus is given to challenges such as high energy consumption, transmission limitations, routing efficiency, storage constraints, deployment complexity and the selection of suitable learning models. The findings highlight that IoT and ML alone are insufficient but, when combined, offer a promising pathway towards intelligent, adaptive and sustainable farming systems for future generations.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"16 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148381155","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

FragCast: A Scalable BLE-Based OTA Framework for Constrained IoT Devices FragCast：用于受限物联网设备的可扩展的基于ble的OTA框架

IF 2.5

IET Wireless Sensor Systems Pub Date : 2026-06-26 DOI: 10.1049/wss2.70031

Ebenezer Djafsia Souboura, Damien Wohwe Sambo, Paul Dayang, Michel Vianney Komguep, Laurent Clavier

{"title":"FragCast: A Scalable BLE-Based OTA Framework for Constrained IoT Devices","authors":"Ebenezer Djafsia Souboura, Damien Wohwe Sambo, Paul Dayang, Michel Vianney Komguep, Laurent Clavier","doi":"10.1049/wss2.70031","DOIUrl":"https://doi.org/10.1049/wss2.70031","url":null,"abstract":"The proliferation of constrained Internet of Things (IoT) devices requires scalable over-the-air (OTA) firmware update mechanisms. Conventional approaches, predominantly based on one-to-one communication, such as Bluetooth Low Energy (BLE) Device Firmware Update (DFU), suffer from a scalability bottleneck that makes fleet-wide updates inefficient and energy-intensive. To address this limitation, this paper proposes FragCast, a broadcast-based OTA dissemination protocol that leverages the one-to-many communication paradigm of BLE advertising channels. The proposed solution implements an application-layer protocol that transports firmware fragments within custom-formatted BLE advertising packets. A detailed simulation framework was developed to analyse the protocol performance under different scanning profiles and fleet sizes of up to 100 devices. The proposed mechanism was also experimentally validated on Arduino UNO R4 Wi-Fi boards equipped with ESP32-S3 modules. Results show that the broadcast architecture enables efficient fleet-wide dissemination, with discovery latency remaining nearly constant as the number of receivers increases. In the evaluated configuration, a fleet of 100 devices can be updated in approximately 40 s using the Aggressive scanning profile and about 90 s using an energy-efficient iOS-like profile. These findings demonstrate that BLE advertising provides a practical and scalable foundation for OTA firmware dissemination in large fleets of constrained IoT devices.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"16 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324799","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

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-05-04

引用次数: 0

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-04-28

引用次数: 0

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-04-14

引用次数: 0

Bioelectrochemical-Augmented Hybrid PV-Battery System for Off-Grid Aquaculture Internet of Things Monitoring 离网水产养殖物联网监测生物电化学增强混合光伏电池系统

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-04-01 DOI: 10.1049/wss2.70027

Afef Bohli, Ridha Bouallegue

{"title":"Bioelectrochemical-Augmented Hybrid PV-Battery System for Off-Grid Aquaculture Internet of Things Monitoring","authors":"Afef Bohli, Ridha Bouallegue","doi":"10.1049/wss2.70027","DOIUrl":"https://doi.org/10.1049/wss2.70027","url":null,"abstract":"Internet of things (IoT)-based monitoring in aquaculture presents significant challenges in remote, off-grid environments where conventional power infrastructure is unavailable. Reliable, continuous and environmentally sustainable energy sources are essential for ensuring autonomous sensor operation and data collection integrity. This study proposes a hybrid energy harvesting system that integrates photovoltaic (PV) panels, lithium-ion batteries and Microbial Fuel Cells (MFCs) as a novel bioelectrochemical energy source for distributed aquaculture monitoring networks. The MFC subsystem (0.01 L flat-plate configuration, operating at 4.7 k<math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>Ω</mi>\u0000 </mrow>\u0000 <annotation> ${Omega }$</annotation>\u0000 </semantics></math> optimal resistance with optimal generated power up to 6.657 nW) generates bioelectrochemical power for parallel battery supplementation. Experimental evaluation under realistic IoT load conditions demonstrates that the bioelectrochemical-augmented hybrid system successfully maintains stable autonomous operation while reducing lithium battery discharge burden by 6.1% throughout complete discharge cycles directly extending battery operational lifespan. This reduction decreases electronic waste, minimises carbon footprint through extended battery lifecycle and reduces pollution and environmental burden. This work demonstrates that bioelectrochemical energy integration is technically viable for aquaculture monitoring and similar off-grid IoT applications, establishing MFCs as a sustainable alternative energy source for greener and more resilient remote sensing infrastructure.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"16 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147682949","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

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-04-01

引用次数: 0

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-03-23

引用次数: 0

A Hybrid Dynamic Sand Cat Swarm Optimisation (HD-SCSO) Approach for Resource Allocation in Wireless Sensor Networks 一种混合动态沙猫群优化（HD-SCSO）无线传感器网络资源分配方法

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-03-23 DOI: 10.1049/wss2.70028

Samer Sindian, Ziad Osman, Abdallah AL-Sabbagh

{"title":"A Hybrid Dynamic Sand Cat Swarm Optimisation (HD-SCSO) Approach for Resource Allocation in Wireless Sensor Networks","authors":"Samer Sindian, Ziad Osman, Abdallah AL-Sabbagh","doi":"10.1049/wss2.70028","DOIUrl":"https://doi.org/10.1049/wss2.70028","url":null,"abstract":"Wireless sensor networks (WSNs) require robust solutions to optimise energy consumption, ensure reliable data transmission and maintain fair resource distribution across large-scale deployments. This paper proposes a hybrid dynamic Sand Cat Swarm Optimisation (HD-SCSO) approach, a bioinspired optimisation framework derived from sand cat adaptive localisation and hunting behaviours. HD-SCSO enhances resource allocation through dynamic sensor node operation adjustments, balanced network workload distribution and optimised data routing to minimise packet loss and extend network lifetime. It operates through three key mechanisms: adaptive cluster organisation, intelligent cluster head selection and real-time adjustments in response to changing network conditions. A security-mathematical model is proposed, which considers the aspect of trust, feedback, probability of cluster heads and conditions of intrusion detection system (IDS) alerts to strengthen resistance to attacks. Simulation results demonstrate that HD-SCSO outperforms existing algorithms, in terms of energy efficiency, packet delivery, network fairness and overall throughput across varying network sizes. Unlike existing algorithms, HD-SCSO integrates trust-based IDS, hybrid sensitivity-driven position updating and unified routing, security and resource allocation, enabling enhanced adaptability and robustness. Its self-optimisation features make it highly suitable for diverse IoT applications, including environmental monitoring, industrial automation and healthcare management, ensuring efficient operation and long-term network sustainability.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":"16 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.70028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147666007","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

IF 2.4

IET Wireless Sensor Systems Pub Date : 2026-03-23

引用次数: 0