Drone and Computer Vision-Based Detection of Aleurothrixus Floccosus in Citrus Crosp

The paradigm of intelligent agriculture has significantly impacted the way in which crops are cared for and maintained. As an alternative, the use of unmanned aerial vehicles (UAVs), or drones, for the purposes of fertilizer application and the prevention of crop pest spread has been proposed. We put forth a solution based on UAVs equipped with computer vision algorithms for the early detection of plants infested with aleurothrixus floccosus in citrus crops. The drone is equipped with a high-definition camera that records the affected plantation, and this video is shared via streaming with a personal computer (PC) that executes the computer vision algorithm to determine the presence or absence of the pest. We selected the open-source real-time object detection and image segmentation model, You Only Look Once (YOLO) version 10s, as a preliminary approach. The numerical results demonstrate that the average precision is 73 % during the training stage and reaches up to 76 % during the operation stage. © 2024 IEEE.