AI-Driven Smart Precision Farming Platform: A Comprehensive Review

Agriculture plays a vital role in ensuring global food security, yet traditional farming methods often suffer from inefficiencies, limited data utilization, and vulnerability to climate variations. The proposed system, Generative AI in Precision Agriculture, aims to revolutionize modern farming through the integration of Artificial Intelligence (AI), Deep Learning, and Data Analytics. The system employs Artificial Neural Networks (ANN) for yield prediction, Generative Adversarial Networks (GAN) for generating synthetic satellite or drone data to overcome missing inputs, and YOLO for pest and disease detection. Additionally, Explainable AI (XAI) using SHAP/LIME ensures transparency of predictions for better farmer understanding. The architecture integrates React Native for mobile accessibility, Flask/FastAPI for backend processing, and MongoDB for secure data storage. This research emphasizes sustainable, data-driven, and technology-enabled agriculture by providing accurate predictions, real-time insights, and multilingual accessibility. The proposed system bridges the gap between AI innovation and practical farming challenges, promoting smart, explainable, and climate-resilient agriculture for the future.