{"title":"基于无线传感器网络的植物病害检测技术研究","authors":"Zhiqing Yang, Hanmin Ye, Yingzhi Liu","doi":"10.1109/IMCEC51613.2021.9481960","DOIUrl":null,"url":null,"abstract":"the plant health status in the region is an important and challenging problem. Aiming at this problem, this paper based on the theory of acoustic emission plant disease stress theory, based on the wireless sensor network (WSN), gathering a wide range of outdoor plants of the acoustic emission signal, the advantage of the characteristics of plant of the acoustic emission signal, through the moving average filter processing, normalization, and similarity, plant health can be divided into health, disease in the early, middle and late four classes. The simulation results show that the method proposed in this paper can be used to accurately, quickly and reliably judge the plant health status in the region.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"33 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Plant Disease Detection Technology Based on Wireless Sensor Network\",\"authors\":\"Zhiqing Yang, Hanmin Ye, Yingzhi Liu\",\"doi\":\"10.1109/IMCEC51613.2021.9481960\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"the plant health status in the region is an important and challenging problem. Aiming at this problem, this paper based on the theory of acoustic emission plant disease stress theory, based on the wireless sensor network (WSN), gathering a wide range of outdoor plants of the acoustic emission signal, the advantage of the characteristics of plant of the acoustic emission signal, through the moving average filter processing, normalization, and similarity, plant health can be divided into health, disease in the early, middle and late four classes. The simulation results show that the method proposed in this paper can be used to accurately, quickly and reliably judge the plant health status in the region.\",\"PeriodicalId\":240400,\"journal\":{\"name\":\"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)\",\"volume\":\"33 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCEC51613.2021.9481960\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCEC51613.2021.9481960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Plant Disease Detection Technology Based on Wireless Sensor Network
the plant health status in the region is an important and challenging problem. Aiming at this problem, this paper based on the theory of acoustic emission plant disease stress theory, based on the wireless sensor network (WSN), gathering a wide range of outdoor plants of the acoustic emission signal, the advantage of the characteristics of plant of the acoustic emission signal, through the moving average filter processing, normalization, and similarity, plant health can be divided into health, disease in the early, middle and late four classes. The simulation results show that the method proposed in this paper can be used to accurately, quickly and reliably judge the plant health status in the region.
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