{"title":"SMART PLANT HEALTH CARE SYSTEM: Image Based Disease Detection and Pesticide Remediation","authors":"Rohan S Savadakar","doi":"10.55041/ijsrem34613","DOIUrl":null,"url":null,"abstract":"Plant and tree populations must be preserved and supported in order to mitigate the growing issues brought about by food and water scarcity brought on by population increase and climate change. The occurrence of plant diseases is a major issue in agriculture as it severely reduces agricultural output. In order to overcome this difficulty, scientists are investigating novel approaches that make use of sensors and imaging to collect data on plant health in order to detect diseases early on. The goal of this project is to create a \"Smart Plant Health Care System\" that combines embedded technologies such as Arduino, Raspberry Pi, and Jetson Nano for pesticide remediation controlled by Arduino and image-based illness diagnosis. More specifically, convolutional neural networks (CNNs) are implemented for real-time illness diagnosis using the processing capacity and adaptability of the Raspberry Pi. Keywords: Smart Agriculture, Plant Health Monitoring, Disease Detection,","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"40 15","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55041/ijsrem34613","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
Plant and tree populations must be preserved and supported in order to mitigate the growing issues brought about by food and water scarcity brought on by population increase and climate change. The occurrence of plant diseases is a major issue in agriculture as it severely reduces agricultural output. In order to overcome this difficulty, scientists are investigating novel approaches that make use of sensors and imaging to collect data on plant health in order to detect diseases early on. The goal of this project is to create a "Smart Plant Health Care System" that combines embedded technologies such as Arduino, Raspberry Pi, and Jetson Nano for pesticide remediation controlled by Arduino and image-based illness diagnosis. More specifically, convolutional neural networks (CNNs) are implemented for real-time illness diagnosis using the processing capacity and adaptability of the Raspberry Pi. Keywords: Smart Agriculture, Plant Health Monitoring, Disease Detection,