Paper Key : IRJ************572
Author: Akshay Gahilod,Chetana Gaikwad,Vedant Walke,Pratiksha Shimbre
Date Published: 15 Nov 2024
Abstract
This project focuses on leveraging technology to enhance agricultural productivity by accurately detecting fruit diseases and providing corresponding fertilizer recommendations. Traditional disease detection methods are manual and require expert intervention, which can be inaccessible for many farmers, especially those in remote regions. This system employs Convolutional Neural Networks (CNNs) to identify diseases in fruit crops using image-based data. Upon detection, it offers customized recommendations for corrective measures, including fertilizer application. By integrating real-time analysis and a user-friendly interface, this system empowers farmers with precise, actionable insights, promoting timely intervention and improving crop health.