Yolo5-Based UAV Surveillance for Tiny Object Detection on Airport Runways

Foreign Object Debris (FOD) present on runways poses a threat to various aircraft components, including the frame, windshield, tires, and engine, while also posing a risk of injury to personnel in the surrounding area. The spectrum of foreign objects includes small rocks, pebbles, nuts, bolts, metal pieces, papers, and objects of millimetric sizes. Currently, a substantial number of air personnel engage in manual runway inspections to identify FOD, a process that demands significant manpower. Conducting visual inspections becomes challenging. An automated object detection framework has been developed to enhance the efficiency of the detection process and minimize dependence on human resources. Utilizing YOLOv5, this study explores Unmanned Aerial Vehicle (UAV) surveillance for precise detection of small objects on airport runways. The focus is on enhancing efficiency and accuracy in monitoring runway spaces prone to Foreign Object Debris (FOD). The integration of YOLOv5 technology offers a robust solution for proactive detection and maintenance of runway safety.