Crop Disease Detection Using ML Health Assistance Chatbot

Authors: Sakshi Sanjay Kapse, Deepali Sanjay Pangavhane, Manasi Kailas Pagare, Om Sandip Dighe, Sayali J Pawar

Country: India

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Abstract: Agriculture is one of the most important sectors, but crop diseases often cause heavy losses for farmers. Many farmers struggle to identify plant diseases at an early stage because it requires expert knowledge and regular monitoring, which is not always available. To solve this problem, we propose a smart system that uses deep learning, specifically a Convolutional Neural Network (CNN), to automatically detect crop diseases from images.In this system, farmers can easily upload a picture of the affected crop through a mobile or web application. The CNN model then analyzes the image and predicts whether the crop is healthy or infected. If a disease is detected, the system provides detailed information about the disease, its symptoms, preventive measures, and the right products (like pesticides or fertilizers) that can help in controlling it. This helps farmers take quick action before the disease spreads further.To make the solution more interactive and farmer-friendly, the system also includes a chatbot. The chatbot allows farmers to ask questions in simple language about crop care, diseases, or best farming practices, and receive instant guidance. By combining image-based disease detection with an AI-powered chatbot, the system not only diagnoses crop health problems but also becomes a 24/7 virtual assistant for farmers.

Keywords: Crop Disease Detection Convolutional Neural Network (CNN) Deep Learning Image Classification Precision Agriculture Chatbot Assistance Smart Farming.

Paper Id: 232813

Published On: 2025-11-12

Published In: Volume 13, Issue 6, November-December 2025

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