Improvement of road safety using YOLO V7 identification

Abstract: Road traffic safety is a crucial concern around the world, the probability of accidents and collisions rises as the number of cars on the road grows. Object detection technology has developed as an effective technique for enhancing road traffic safety. This research provides a detailed evaluation of the most current breakthroughs in object recognition systems and their applications in road traffic safety. The paper opens by providing an overview of the issues and risks involved with road traffic, highlighting the importance of enhanced safety measures. It then digs into a full review of object identification strategies, ranging from traditional methods to cutting-edge deep learning models, demonstrating their capacities to identify vehicles, pedestrians, cyclists, and other road items.It investigates how these technologies improve real-time monitoring, collision avoidance, and traffic management. Furthermore, the article looks into object detection for traffic law enforcement and monitoring, emphasizing its significance in improving security and lowering accidents. It outlines prospective future research directions, such as the development of powerful, real-time object detection systems and their application to smart city initiatives.

Keywords: Real-time object detection, road traffic safety, bounding boxes,intersection over Union (IOU), Anchor boxes, non-max Suppression.