G. Maheswari, A. A. Lakshmi, K. K. Valli, G. Rajkumar, S. Ramesh
{"title":"Edge Sensing of Agricultural Layers with Signals and TS Protocol and PS with PAPRAware Transmission","authors":"G. Maheswari, A. A. Lakshmi, K. K. Valli, G. Rajkumar, S. Ramesh","doi":"10.1109/ICNWC57852.2023.10127247","DOIUrl":null,"url":null,"abstract":"Efficient data collection using wireless sensor networks (WSN) today focuses on the hot topics of smart agriculture and precision farming. Agricultural WSNs, however, often face many problems, including multitasking, variability, and transmission rate. In this paper, we provide a practical solution that takes advantage of the many data collection tasks in smart farming enabled by wireless sensor networks created enabled by edge computing. The next phase is a cutting-edge data collection system that combines edge computing and wireless sensor technology. The data collection system is made by modeling a variety of sensors and processes. The optimal workstation and wireless sensor are then selected on the edges of the network server, taking into consideration each unique job and the relationship between both the task and the sensor, to satisfy the accuracy of the information and the time constraints of information-gathering activities. We also design a data collection procedure that takes into consideration established criteria for information accuracy. Eventually, when the new technique is implemented, a simulation model is built and effects are evaluated and contrasted with conventional approaches. The idea outperforms the conventional approaches in metrics, according to the comparative results.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Networking and Communications (ICNWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNWC57852.2023.10127247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Efficient data collection using wireless sensor networks (WSN) today focuses on the hot topics of smart agriculture and precision farming. Agricultural WSNs, however, often face many problems, including multitasking, variability, and transmission rate. In this paper, we provide a practical solution that takes advantage of the many data collection tasks in smart farming enabled by wireless sensor networks created enabled by edge computing. The next phase is a cutting-edge data collection system that combines edge computing and wireless sensor technology. The data collection system is made by modeling a variety of sensors and processes. The optimal workstation and wireless sensor are then selected on the edges of the network server, taking into consideration each unique job and the relationship between both the task and the sensor, to satisfy the accuracy of the information and the time constraints of information-gathering activities. We also design a data collection procedure that takes into consideration established criteria for information accuracy. Eventually, when the new technique is implemented, a simulation model is built and effects are evaluated and contrasted with conventional approaches. The idea outperforms the conventional approaches in metrics, according to the comparative results.