Vehicle airport runway FOD assisted intelligent identification system

As airport facilities upgrade and the demand for air transportation increases, solving the problem of runway safety becomes particularly important. In order to ensure the safe takeoff and landing of aircraft, Foreign Object Debris (FOD) on the runway should be accurately and quickly detected during runway detection to reduce the probability of danger. At present, FOD detection of most airport runways still adopts the traditional manual inspection, which has low efficiency and high cost. An intelligent recognition system for vehicle-mounted FOD management based on YOLOv8 was proposed in this paper, applicable to real airport scenarios, and details the design of the system's core algorithm, emphasizing the YOLOv8 framework in the detection module. A new data enhancement algorithm is proposed to ensure the high performance of the system under complex environment changes. The experimental results show that the accuracy rate of the system is higher than 95%, and it demonstrates strong robustness in complex scenes.