P. Varalakshmi, B. Y. Sivashakthivadhani, B. L. Sakthiram
{"title":"Automatic Plant Escalation Monitoring System Using IoT","authors":"P. Varalakshmi, B. Y. Sivashakthivadhani, B. L. Sakthiram","doi":"10.1109/ICCCT2.2019.8824969","DOIUrl":null,"url":null,"abstract":"Agriculture plays a crucial role in the Indian economy. It not only provides food and raw material but also provides employment opportunities and also helps in monitoring gas exchange problems, rainfall percolation and microbial activity. Hence it is important to find a technique which will classify infectious plant from healthy plant, in order to cure the diseased plant at early stages and also improve the yield of the agriculture. An hardware model is built using the Raspberry Pi 3 to indicate to the farmer about the temperature, pressure and soil moisture level when it goes below or above a threshold values. A new classification technique is developed based on the convolutional neural network (CNN) to classify infectious plant from the healthy plant and its efficiency is compared with SVM,KNN classifier and random forest.","PeriodicalId":445544,"journal":{"name":"2019 3rd International Conference on Computing and Communications Technologies (ICCCT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 3rd International Conference on Computing and Communications Technologies (ICCCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCT2.2019.8824969","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Agriculture plays a crucial role in the Indian economy. It not only provides food and raw material but also provides employment opportunities and also helps in monitoring gas exchange problems, rainfall percolation and microbial activity. Hence it is important to find a technique which will classify infectious plant from healthy plant, in order to cure the diseased plant at early stages and also improve the yield of the agriculture. An hardware model is built using the Raspberry Pi 3 to indicate to the farmer about the temperature, pressure and soil moisture level when it goes below or above a threshold values. A new classification technique is developed based on the convolutional neural network (CNN) to classify infectious plant from the healthy plant and its efficiency is compared with SVM,KNN classifier and random forest.