Rider surveillance to ensure wearing of helmet and to assistpatrol for safety drive using deep learning approaches

Road safety is a major concern in today’s world, and the use of helmets while driving two-wheelers is an important measureto reduce the risk of head injuries. The identification of vehicles through their number plates is an important aspect of law enforcement. In this paper, we propose an automatic helmet and dirty number plate identification using computer vision techniques and deep learning. The system employs object detection algorithms to detect helmets and number plates in real-time images captured by a camera. The proposed system can accurately detect the presence or absence of helmets on riders and read the number plates of vehicles. The system’seffectiveness was demonstrated through experiments on a large dataset of images, and the results showed that the proposed system achieves high accuracy and fast processing speed. The proposed system has the potential to be integrated into existing traffic surveillance systems to improve road safety and law enforcement.