K. Devi Priya, A. S. Samyogitha, A. K. Krishna Reddy, B. Divya Sri
{"title":"集成cropiify -作物和肥料推荐系统与叶片病害预测","authors":"K. Devi Priya, A. S. Samyogitha, A. K. Krishna Reddy, B. Divya Sri","doi":"10.1109/ICIDCA56705.2023.10100117","DOIUrl":null,"url":null,"abstract":"In India, farming is the most popular occupation. It has a significant impact on the Indian economy and offers plenty of employment prospects to Indians. Nowadays, farmers do not choose the best crop for each soil type. The yields from agriculture are directly impacted. Farmers in the area are suffering severe financial losses as a result. There are now a lot of considerations to consider while cultivating a specific sort of crop on a specific type of soil. Numerous soil variables are considered to choose the best crop to grow. This innovative opinion mining approach will take factors like soil moisture content, pressure, and temperature. To estimate the ideal crop, this prediction model would in fact use machine learning algorithms. The optimal fertilizer will also be suggested based on the soil moisture levels, pH value, temperature, and crop-related environmental circumstances. The best fertilizer will be suggested using this innovative system for fertilizer recommendations in order to produce the best harvests. This application uses deep neural networks to forecast leaf disease. To determine whether leaf image in the system contains diseases, the test set is being examined. If leaf does not have any disease it is said to be normal. Otherwise, the leaf is infected, and crop disease treatment is promptly advised.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"ENSEMBLED CROPIFY – Crop & Fertilizer Recommender System with Leaf Disease Prediction\",\"authors\":\"K. Devi Priya, A. S. Samyogitha, A. K. Krishna Reddy, B. Divya Sri\",\"doi\":\"10.1109/ICIDCA56705.2023.10100117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In India, farming is the most popular occupation. It has a significant impact on the Indian economy and offers plenty of employment prospects to Indians. Nowadays, farmers do not choose the best crop for each soil type. The yields from agriculture are directly impacted. Farmers in the area are suffering severe financial losses as a result. There are now a lot of considerations to consider while cultivating a specific sort of crop on a specific type of soil. Numerous soil variables are considered to choose the best crop to grow. This innovative opinion mining approach will take factors like soil moisture content, pressure, and temperature. To estimate the ideal crop, this prediction model would in fact use machine learning algorithms. The optimal fertilizer will also be suggested based on the soil moisture levels, pH value, temperature, and crop-related environmental circumstances. The best fertilizer will be suggested using this innovative system for fertilizer recommendations in order to produce the best harvests. This application uses deep neural networks to forecast leaf disease. To determine whether leaf image in the system contains diseases, the test set is being examined. If leaf does not have any disease it is said to be normal. Otherwise, the leaf is infected, and crop disease treatment is promptly advised.\",\"PeriodicalId\":108272,\"journal\":{\"name\":\"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIDCA56705.2023.10100117\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIDCA56705.2023.10100117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ENSEMBLED CROPIFY – Crop & Fertilizer Recommender System with Leaf Disease Prediction
In India, farming is the most popular occupation. It has a significant impact on the Indian economy and offers plenty of employment prospects to Indians. Nowadays, farmers do not choose the best crop for each soil type. The yields from agriculture are directly impacted. Farmers in the area are suffering severe financial losses as a result. There are now a lot of considerations to consider while cultivating a specific sort of crop on a specific type of soil. Numerous soil variables are considered to choose the best crop to grow. This innovative opinion mining approach will take factors like soil moisture content, pressure, and temperature. To estimate the ideal crop, this prediction model would in fact use machine learning algorithms. The optimal fertilizer will also be suggested based on the soil moisture levels, pH value, temperature, and crop-related environmental circumstances. The best fertilizer will be suggested using this innovative system for fertilizer recommendations in order to produce the best harvests. This application uses deep neural networks to forecast leaf disease. To determine whether leaf image in the system contains diseases, the test set is being examined. If leaf does not have any disease it is said to be normal. Otherwise, the leaf is infected, and crop disease treatment is promptly advised.