Rover Based Early Warning System for Plant Disease

This project presents an autonomous rover designed to detect wheat diseases in real time using machine learning. A CNN model was developed in MATLAB for accurate disease identification from images captured by the ESP32 Cam on the rover. The system integrates multiple sensors, including ultrasonic sensors for obstacle avoidance and soil moisture sensors for environmental monitoring. Powered by an onboard battery and controlled by a microcontroller, the rover navigates fields autonomously, reducing manual labor and enhancing precision agriculture. This solution promotes sustainable farming by improving crop management and minimizing yield loss.