A collaborative WSN‐IoT‐Animal for large‐scale data collection

IF 2.1 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Hamayadji Abdoul Aziz, Ado Adamou Abba Ari, Arouna Ndam Njoya, Asside Christian Djedouboum, Alidou Mohamadou, Ousmane Thiaré
{"title":"A collaborative WSN‐IoT‐Animal for large‐scale data collection","authors":"Hamayadji Abdoul Aziz, Ado Adamou Abba Ari, Arouna Ndam Njoya, Asside Christian Djedouboum, Alidou Mohamadou, Ousmane Thiaré","doi":"10.1049/smc2.12089","DOIUrl":null,"url":null,"abstract":"In recent years, large‐scale data collection systems have developed rapidly in many fields, including agriculture, transport and many others. The internet of things (IoT), whose main platform is wireless sensor networks (WSNs), is behind this development. Comprising thousands of sensors of different kinds, their main purpose is to collect and transmit data. Several data collection techniques have been proposed, including static, mobile and hybrid approaches. The challenges faced by these techniques are considerable, and include energy conservation, planning and trajectory optimisation during data collection, most importantly, the challenges related to the communication between the static sensors generally distributed in a more or less large geographical space and the mobile data collection system (UAV, vehicle, robot etc.). Not to mention the cost, which remains enormous for the agricultural sectors. A hybrid WSN‐IoT‐Animal that is self‐configured to improve data acquisition over large agricultural areas is presented. The main objective and originality of the heterogeneous semi‐modern scheme proposed here oscillating between traditional agriculture and precision agriculture is the use of animals as data collection tools. The main contribution here is the design of a simple and efficient model of data collection that is easily accessible by farmers by adapting the available resources. This model describes and adopts a sensor deployment method based on the notion of the hypergraph, which provides adequate coverage and ensures communication between the mobile sink and a subset of peripheral sensors chosen in alternation. Simulation results verify the effectiveness of the proposed protocol in terms of network lifetime compared to other works. In addition, the amount of data received by the mobile sink demonstrates the importance of this approach in terms of connectivity for large‐scale data collection.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Smart Cities","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/smc2.12089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

In recent years, large‐scale data collection systems have developed rapidly in many fields, including agriculture, transport and many others. The internet of things (IoT), whose main platform is wireless sensor networks (WSNs), is behind this development. Comprising thousands of sensors of different kinds, their main purpose is to collect and transmit data. Several data collection techniques have been proposed, including static, mobile and hybrid approaches. The challenges faced by these techniques are considerable, and include energy conservation, planning and trajectory optimisation during data collection, most importantly, the challenges related to the communication between the static sensors generally distributed in a more or less large geographical space and the mobile data collection system (UAV, vehicle, robot etc.). Not to mention the cost, which remains enormous for the agricultural sectors. A hybrid WSN‐IoT‐Animal that is self‐configured to improve data acquisition over large agricultural areas is presented. The main objective and originality of the heterogeneous semi‐modern scheme proposed here oscillating between traditional agriculture and precision agriculture is the use of animals as data collection tools. The main contribution here is the design of a simple and efficient model of data collection that is easily accessible by farmers by adapting the available resources. This model describes and adopts a sensor deployment method based on the notion of the hypergraph, which provides adequate coverage and ensures communication between the mobile sink and a subset of peripheral sensors chosen in alternation. Simulation results verify the effectiveness of the proposed protocol in terms of network lifetime compared to other works. In addition, the amount of data received by the mobile sink demonstrates the importance of this approach in terms of connectivity for large‐scale data collection.
用于大规模数据收集的 WSN-IoT-Animal 协作系统
近年来,大规模数据收集系统在农业、交通等许多领域迅速发展。物联网(IoT)是这一发展的幕后推手,其主要平台是无线传感器网络(WSN)。WSN 由成千上万个不同种类的传感器组成,其主要目的是收集和传输数据。目前已提出了多种数据收集技术,包括静态、移动和混合方法。这些技术所面临的挑战相当大,包括数据收集过程中的能源节约、规划和轨迹优化,最重要的是与一般分布在或多或少较大地理空间的静态传感器和移动数据收集系统(无人机、车辆、机器人等)之间的通信有关的挑战。更不用说对于农业部门来说仍然巨大的成本了。本文介绍了一种 WSN-IoT-Animal 混合系统,该系统可自行配置,以改进大面积农业区的数据采集。本文提出的在传统农业和精准农业之间摇摆的异构半现代方案的主要目标和独创性在于将动物作为数据采集工具。该方案的主要贡献在于设计了一种简单高效的数据采集模式,农民可以通过调整现有资源轻松获取数据。该模型描述并采用了一种基于超图概念的传感器部署方法,它能提供足够的覆盖范围,并确保移动水槽与交替选择的外围传感器子集之间的通信。仿真结果验证了所提协议在网络寿命方面的有效性。此外,移动汇接收到的数据量也证明了这种方法在大规模数据收集的连接性方面的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IET Smart Cities
IET Smart Cities Social Sciences-Urban Studies
CiteScore
7.70
自引率
3.20%
发文量
25
审稿时长
21 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信