Helmet Regulation

Helmet regulation enforcement is increasingly reliant on automated systems for real-time detection of violations, primarily focusing on improving the accuracy and speed of motorcycle helmet detection in video footage. Current research heavily utilizes deep learning models, particularly variations of the YOLO architecture (YOLOv5, YOLOv8), often enhanced with techniques like genetic algorithms and data augmentation to improve performance in challenging conditions. These advancements aim to improve road safety by enabling efficient monitoring and enforcement of helmet laws, potentially leading to a reduction in motorcycle-related injuries and fatalities.