Kowshik Kolvekar, Sahil Lotlikar, M. Naik, Ashwin Faldesai, Yeshudas Muttu, M. Colaco
{"title":"Cayenne based Plant Monitoring Control System","authors":"Kowshik Kolvekar, Sahil Lotlikar, M. Naik, Ashwin Faldesai, Yeshudas Muttu, M. Colaco","doi":"10.1109/IBSSC51096.2020.9332186","DOIUrl":null,"url":null,"abstract":"India is the world’s major producer of various agricultural materials like fruits, vegetables, pulses, etc. Tomato is the most widely cultivated crop in India making it the most profitable agribusiness. Until industrial revolution, almost two-third of the human residents depends only on farming. For major development & solidification of India’s agriculture, research and extension system is one of the most vital needs for agricultural development. If agriculture is to be safe, healthy & sustainable, it is essential to have healthy crops as they play an important role in generating sufficient quantities of healthy foods & contribute to the quality of life. Hence, for the increased production, suitable evaluation of crop disease in the field is very critical. Tomato horticulture farmers face lots of problems out of which leaf disease is of major concern because it happens at the earlier stage of the plant growth and if not treated on time it can destroy the full cultivation. This paper focuses on monitoring the tomato crop plantation and tomato leaf disease classification using image processing techniques and artificial neural networks. With this system farmer will now be able to view his farm and will be able to take control actions based on the measured parameters stored onto the cloud making the system very efficient.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"690 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Bombay Section Signature Conference (IBSSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBSSC51096.2020.9332186","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
India is the world’s major producer of various agricultural materials like fruits, vegetables, pulses, etc. Tomato is the most widely cultivated crop in India making it the most profitable agribusiness. Until industrial revolution, almost two-third of the human residents depends only on farming. For major development & solidification of India’s agriculture, research and extension system is one of the most vital needs for agricultural development. If agriculture is to be safe, healthy & sustainable, it is essential to have healthy crops as they play an important role in generating sufficient quantities of healthy foods & contribute to the quality of life. Hence, for the increased production, suitable evaluation of crop disease in the field is very critical. Tomato horticulture farmers face lots of problems out of which leaf disease is of major concern because it happens at the earlier stage of the plant growth and if not treated on time it can destroy the full cultivation. This paper focuses on monitoring the tomato crop plantation and tomato leaf disease classification using image processing techniques and artificial neural networks. With this system farmer will now be able to view his farm and will be able to take control actions based on the measured parameters stored onto the cloud making the system very efficient.