{"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.