AI-Driven Decision Support System for Agriculture

Agriculture plays a crucial role in food security and economic growth, and optimizing farming decisionscan significantly improve productivity. This project presents a comprehensive system for croprecommendation, fertilizer recommendation, and plant disease prediction using advanced machine learningtechniques. The crop recommendation module employs a Random Forest classifier to suggest the mostsuitable crop based on soil parameters, climate conditions, and environmental factors. The fertilizerrecommendation system provides optimal nutrient suggestions tailored to crop and soil needs. Additionally,a Convolutional Neural Network (CNN) is utilized for disease prediction by analysing leaf images, enablingearly detection and management of plant diseases. This integrated approach aims to assist farmers in makingdata-driven decisions to enhance yield, reduce resource wastage, and ensure sustainable agriculturalpractices.