Crop Disease Prediction and Management System

Abstract -Agriculture plays a critical role in ensuring food security, economic stability, and environmental sustainability. As the demand for higher crop yields intensifies, efficient resource management—particularly fertilizer use—has become essential. The Precision Fertilizer Management project addresses this challenge by utilizing machine learning techniques, specifically Random Forest Regression, to optimize fertilizer application. By analyzing data on soil quality, crop yield, weather patterns, and rainfall, the system generates precise, data-driven recommendations tailored to specific crop needs. This approach minimizes fertilizer waste, reduces environmental impact, and supports sustainable farming practices. With a user-friendly interface and cloud-based accessibility, the project provides a practical, scalable solution for eco-friendly agriculture, even in regions with limited internet access.