Helmet Detection System Using YOLOv8

Helmet usage remains an important motorcycle safety concern globally because it reduces the risk of head injuries. This study investigates the use of YOLOv8, an advanced object detection algorithm, to detect helmet usage among motorcyclists in real-time. This study proposes an automated solution for monitoring and enforcing helmet compliance, benefitting from YOLOv8s superior accuracy and speed. The study outlines dataset preparation, model training, and real-time deployment, attesting to the versatility YOLOv8 allows in diverse environments. The results indicate the high accuracy and effectiveness of the system in more challenging conditions. The findings reveal that YOLOv8based systems could prove effective in providing useable interventions to improve public road safety.