CROPGUARD: AI-POWEREDREAL-TIME CROP DISEASE DETECTION AND PRECISION PESTICIDE SPRAYER

Abstract

Crop diseases are a major challenge to agricultural productivity and sustainable farming. Early detection and proper treatment of plant diseases are essential to reduce crop loss and improve yield. Traditional methods of detecting crop diseases mainly depend on manual inspection by farmers or experts, which can be time-consuming, labor-intensive, and sometimes inaccurate. This project presents an intelligent robotic system called CropGuard for real-time crop disease detection and precision pesticide spraying using artificial intelligence and embedded systems.The proposed system captures images of crop leaves using an ESP32-CAM module while the robot moves through the farming field. The captured images are processed using a trained machine learning model that analyzes the plant condition and classifies it into three categories: healthy crop, low disease infection, or high disease infection. Based on the classification result, the system automatically activates a precision pesticide sprayer to spray chemicals only on the affected plants. This targeted spraying method helps reduce excessive pesticide usage and minimizes environmental damage.The robot is powered by a 12V battery supported by an 8V solar panel, making it suitable for long-term field operation. Navigation is controlled using an ESP32 microcontroller and motor driver, and a blue mat placed at the end of the field helps the robot detect the boundary and return automatically. The proposed system provides an efficient and low-cost solution for smart agriculture by enabling automated disease detection, reducing human effort, and improving crop management.