Real Time Helmet Violation Detection

Real-time helmet violation detection systems aim to improve road safety by automatically identifying motorcycle riders and passengers not wearing helmets. Current research heavily utilizes deep learning object detection models, particularly variations of YOLO (You Only Look Once), often enhanced with techniques like genetic algorithms and data augmentation to improve accuracy and real-time performance. These systems are evaluated using metrics such as mean Average Precision (mAP), and their successful implementation in real-world settings holds significant potential for enforcing helmet laws and reducing motorcycle-related injuries.