Published Paper Details:

Agriculture plays a significant role in the Indian economy, especially in states like Maharashtra where a large population depends on farming for livelihood. Farmers often face challenges such as improper crop selection, crop diseases, uncertain weather conditions, low profitability, and lack of awareness about crop insurance schemes. Most existing agricultural systems focus on individual services and do not provide an integrated solution for farmers. This paper presents CropGenius, an integrated AI-based smart farming assistance system developed using Machine Learning, Deep Learning, and web technologies. The system recommends suitable crops based on district, season, soil type, irrigation method, and land size using a Random Forest model. It also detects crop diseases from uploaded leaf images using CNN and TensorFlow Lite models. Additional features include yield and profit estimation, crop comparison, Smart Bima insurance recommendation, multilingual support, and expert chat assistance. The system is implemented using Flask, SQLite, Scikit-learn, TensorFlow, OpenCV, and Tailwind CSS. CropGenius combines multiple agricultural services into a single user-friendly platform to improve farming decisions, reduce crop losses, and increase farmer accessibility to digital agricultural support systems.