Development of Object Detection System on Non-Helmed Riders Using YOLOv8

Abstract

Motorcycle accidents are a severe problem, with the number of incidents reaching 66,602 in 2023. Helmets as head protection are mandatory, but awareness of their use is still low. This research utilises Deep Learning, specifically YOLOv8, to detect helmet use violations among motorbike riders. The research results show high accuracy with a Precision of 89.5%, Recall at 78.4%, and mAP50 at 85.7%. YOLOv8 effectively detects violations and provides a solid basis for increasing motorist awareness. Through this innovative approach, it is hoped that a safer driving culture and collective awareness of responsibility in traffic safety will be created.