This project provides a comprehensive agricultural plant disease detection and advisory platform that uses multi-stakeholder collaboration to revolutionize farming practices in India. The method uses TensorFlow-based deep learning models to accurately identify plant diseases from leaf photos, achieving 98.2% classification accuracy across key crops. The platform has a multilingual interface that supports regional languages, allowing varied farming communities to access innovative agricultural technology. Real-time disease diagnosis, personalized fertilizer and pesticide recommendations, a fully integrated e-commerce marketplace, expert consultation networks, weather integration, field logging analytics, and precision agriculture tools are among the core features. A comprehensive digital ecosystem serves a diverse range of stakeholders, including farmers, agricultural input suppliers, and agricultural professionals. Implementation of a web interface, data visualization, and weather integration. The platform addresses major issues in Indian agriculture, such as limited access to expert information, language obstacles, supply chain inefficiencies, and a scarcity of precision agricultural instruments. Improved crop health management, lower agricultural losses, better farmer decision-making, increased access to agricultural expertise, and data-driven insights lead to more sustainable farming practices.

Keywords: Precision agriculture, multilingual platform, deep learning, digital agriculture, farmer advice system.