A. N, Jaimy James Poovely, Abhijith Surendran, Samuel Sabu Thomas
{"title":"Tomato Plant Health Management Using AI","authors":"A. N, Jaimy James Poovely, Abhijith Surendran, Samuel Sabu Thomas","doi":"10.1109/ACCESS57397.2023.10199392","DOIUrl":null,"url":null,"abstract":"India is a country whose economy is heavily reliant on agriculture. The agriculture sector accounts for a significant portion of the country's overall economy. Plant diseases are particularly important because they can have a negative impact on the quality and quantity of crops. Viruses, bacteria, fungi, and other microorganisms can cause plant diseases. The majority of farmers are completely unaware of such diseases. In India, the tomato crop is a common staple due to its high commercial value and strong production potential. In tomatoes, the three most potent antioxidants are vitamin E, vitamin C, and beta-carotene. The main focus of the proposed article is to create a more accurate and time-efficient automatic method for detecting tomato plant leaf diseases. This work aims to create a system that captures images with a Raspberry Pi camera and classifies them using Convolutional Neural Network. In neural network models, automatic feature extraction is utilized to help classify input photos into appropriate illness categories.","PeriodicalId":345351,"journal":{"name":"2023 3rd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS)","volume":"136 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 3rd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACCESS57397.2023.10199392","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 a country whose economy is heavily reliant on agriculture. The agriculture sector accounts for a significant portion of the country's overall economy. Plant diseases are particularly important because they can have a negative impact on the quality and quantity of crops. Viruses, bacteria, fungi, and other microorganisms can cause plant diseases. The majority of farmers are completely unaware of such diseases. In India, the tomato crop is a common staple due to its high commercial value and strong production potential. In tomatoes, the three most potent antioxidants are vitamin E, vitamin C, and beta-carotene. The main focus of the proposed article is to create a more accurate and time-efficient automatic method for detecting tomato plant leaf diseases. This work aims to create a system that captures images with a Raspberry Pi camera and classifies them using Convolutional Neural Network. In neural network models, automatic feature extraction is utilized to help classify input photos into appropriate illness categories.