CROP RECOMMENDATION SYSTEM

The global demand for sustainable and efficient agricultural practices is rising due to food security challenges, population growth, and environmental sustainability concerns. Among the critical issues, fertilizer mismanagement contributes to soil degradation, water contamination, greenhouse gas emissions, and reduced crop productivity. To address these challenges, this research presents Cloud Farm, a cloud-based, machine learning-driven system designed to deliver intelligent, site-specific fertilizer recommendations. The platform analyzes soil nutrient values (N, P, K), pH, rainfall, and crop requirements using supervised learning models such as Random Forest and Gradient Boosting, achieving higher accuracy than conventional methods. Cloud Farm incorporates multilingual user interfaces to enhance accessibility for farmers across diverse regions and includes an integrated e-commerce module for seamless fertilizer procurement.