AI Powered Crop Rotation

This project presents a Crop Rotation Recommen- dation System using the Rule Learning Crop Optimizer (RLCO) approach. The system is designed to suggest suitable crops by applying rule-based logic derived from agricultural knowledge. It uses simple and understandable rules to analyze inputs like soil type, weather conditions, and crop history in order to recommend the next appropriate crop for cultivation.The proposed system helps farmers in making better crop planning decisions by reducing the risk of soil nutrient depletion and improving overall productivity. Since the recommendations are based on clear rules, the system is easy to understand and practical to use. This project aims to support sustainable farming practices and assist farmers with an effective decision-support tool for crop rotation planning.