AI Smart Farming System

Agriculture is the backbone of India’s rural econ- omy, providing livelihood to nearly 60% of the population. However, productivity is often affected due to plant diseases, unpredictable climate, soil nutrient imbalance, and lack of timely expert guidance. To overcome these challenges, this paper proposes the AI Smart Farming System, a web-based decision- support system that integrates machine learning, deep learning, weather intelligence, multilingual chatbot services, community forums, and fertilizer optimization models. The system uses a CNN model for image-based crop disease detection, a hybrid rule- based and machine-learning method for fertilizer recommenda- tion, and global weather APIs for climate forecasting. The paper discusses the complete methodology, architecture, mathematical models, algorithms, evaluation metrics, and future scalability. The proposed system aims to digitize and modernize farming practices to support rural farmers, reduce crop loss, and improve productivity.