CROPIC - AI Based Plant Disease Detection

CROPIC - AI Based Plant Disease Detection presents an end-to-end artificial intelligence framework for accurate, real-time plant disease diagnosis. The system integrates a Convolutional Neural Network (CNN) model with a mobile-first web interface to enable farmers, gardeners, and nursery owners to easily detect plant diseases from images. The AI model, developed using TensorFlow and Keras, processes leaf images through preprocessing (resizing to 256×256 and normalization), feature extraction, and classification using Softmax-based dense layers. The system achieves a training accuracy of 98% and validation accuracy of 97%, demonstrating strong generalization performance. The full-stack architecture employs a React frontend for user interaction and a Flask backend API for AI model integration, resulting in a lightweight, accessible, and scalable diagnostic tool. Beyond classification, CROPIC aims to extend its capabilities through Retrieval-Augmented Generation (RAG) pipelines and environmental data integration for personalized plant care insights. This research showcases the power of combining modern web technologies with deep learning to create sustainable, accessible solutions for precision agriculture and horticultural diagnostics.