Leaf Sense: AI Powered System for Plant Disease Diagnosis and Personalized Care

The project aims to build an AI-driven plant disease prediction and diagnosis system that not only identifies plant diseases from images but also provides tailored treatment recommendations based on contextual data. The system incorporates convolutional neural networks (CNNs) to take into account other parameters such as plant type, planting history, pesticide applications, and environmental conditions to provide personalized solutions.The backend utilizes Python along with powerful libraries such as TensorFlow and Keras for image classification and predictive analytics. The Flask framework powers the web-based interface, ensuring efficient communication between the user and the system. The frontend designed using HTML, CSS, and JavaScript provides an interactive and user-friendly experience. To support long-term data storage and predictive improvements, the system integrates a reliable MySQL database to store user information and plant records for ongoing monitoring.This comprehensive platform provides real- time disease identification, actionable treatment recommendations and advanced monitoring capabilities, making it an invaluable tool for gardeners, farmers and plant enthusiasts. By simplifying decision-making and enhancing plant care management, the project highlights the transformative role of i in modern agriculture.