A Road Traffic Surveillance Model for Wide Range Helmet Usage Sensing and Number Plate Recall Using Integrated Deep Learning Model
摘要
Improving road safety can be done by using advanced technology such as YOLOv8 helmet detection and number plate reading. This can help in imposing helmet laws and catching the violators which can help the authorities to identify and penalize them. Such procedure would encourage accountability, reduce accidents, and create safer road environments for everyone. YOLOv8 is an advanced object, it uses deep learning to detect helmets and number plates of traffic violators easily and accurately. By studying the video streams or images, YOLOv8 can detect helmet wearing status and read the number plates with precision, thus improving traffic surveillance and law enforcement efficiency as well as promoting road safety.