Wheat Disease Detection and Multilingual Agricultural Assistance System Project

Agriculture plays a vital role in the economy, and early disease detection is essential for improving crop yield and reducing losses. This project presents an AI-Based Wheat Disease Detection and Multilingual Agricultural Assistance System that utilizes deep learning techniques to identify wheat diseases from leaf images. Farmers can upload crop images through a web application, where a trained Convolutional Neural Network (CNN) classifies the disease category. Based on the prediction, the system provides treatment recommendations through an AI-powered chatbot. To ensure accessibility for farmers from different regions, the chatbot supports multiple languages including English, Malayalam, Tamil, and Hindi. The proposed system enables quick disease diagnosis, accurate treatment guidance, and improved decision-making for sustainable farming practices.