Cloud-Based AI-Enabled Crop Disease Identification and Advisory System

Around the world, plant diseases have significantly affected agricultural productivity and food security. Detecting these diseases early and accurately gives farmers a better chance to minimize crop loss and take timely action. Traditionally, plant disease identification relied on experts visually inspecting the affected plants. However, this method is slow, expensive, and depends heavily on the availability of trained experts. In many rural areas, such experts are hard to access, and even when available, visual inspection can still lead to inaccurate results. In this paper, we present an AI-powered plant disease detection system that uses Convolutional Neural Networks (CNNs). The system automatically analyzes leaf images and identifies whether the plant is healthy or diseased with high accuracy. To make the solution accessible, we developed a web-based application where users can upload a picture of a plant leaf and receive instant predictions along with confidence scores. The back-end is implemented using FastAPI, while the front-end is built with React and TypeScript. Our experimental findings show that the proposed system performs efficiently, providing real-time predictions for new, unseen images with strong accuracy. Additionally, the system is scalable, user-friendly, and highly suitable for agricultural environments.