Demonstrates real-time wheat disease detection in local farms, suggesting improved agricultural practices.
This research paper presents CropCare Robot, an AI-based autonomous drone system developed for real-time wheat disease detection and crop monitoring. The system uses an ESP32-CAM module mounted on a drone to capture field images, which are processed using a YOLOv9 object detection model integrated with a Flask backend API. MongoDB is used to store user information, disease detection records, image references, confidence values, and timestamps. The application supports user registration, login, image-based wheat disease detection, manual drone control, autonomous path planning, treatment recommendations, analytics, and detection history. Functional testing was conducted for user authentication, disease detection, drone control, autonomous monitoring, and data storage. The work aims to reduce manual crop inspection and support early wheat disease detection for smart agriculture in local farming conditions.
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Shahbaz et al. (2026) studied this question.
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