Next-Gen Precision Farming Using Multimodal AI and Geospatial Intelligence

Abstract

Global food security means agriculture must grow and become more modern. Most other industries have changed course to adapt with the era of new technological changes, especially AI, but farming has not. Our effort to alter this is by presenting the system here: Integrating Generative AI in Precision Agriculture. The system will use AI, Deep Learning, and Advanced Data Analytics to change the core of farming practices. For yield prediction, the system uses Artificial Neural Networks, Generative Adversarial Networks synthesizes missing satellite or drone data, and the YOLO System which detects pests and diseases. Furthermore, Explainable AI (XAI) with SHAP and LIME provides transparency so farmers understand the predictions. React Native is used for mobile access, the backend is Flask/FastAPI and MongoDB is used for data security. This research focuses on responsible and sustainable AgriTech and tech agriculture by offering accurate forecasts and real-time insights with multilingual access. By proposing this system, the disconnect between AI cutting-edge development and everyday farming concerns is narrowed. This application will definitely impact in future.