AUTOMATIC DETECTION OF MOTOR VEHICLE OFFENDERS USING COMPUTER VISION AS PART OF A CYBER-PHYSICAL EMERGENCY PREVENTION SYSTEM

Abstract

In today's world, where the pace of technological development is accelerating, road safety remains a pressing issue. Automation of processes and the use of the latest technologies in the field of road traffic can help reduce the number of accidents and violations of the rules. Automatic detection of motorists using computer vision as part of a cyber-physical accident prevention system is a promising area of research aimed at ensuring comfortable and safe road traffic. However, for the effective implementation of this technology, a number of technical and organizational issues need to be addressed.

This article will investigate the role of computer vision in detecting automotive offenders and consider the implementation of cyber-physical systems aimed at preventing road accidents. The problem of improving the quality of image reading for effective detection of objects using computer vision to ensure safety standards was considered.

The article also includes an analysis of the technologies, methods and issues involved. In particular, the article explores the possibilities of using artificial intelligence and neural networks in computer vision to increase the speed and accuracy of intrusion detection. The purpose of the study is to determine the advantages and prospects for further development of road violator detection systems, in particular, their contribution to improving road safety and the possibility of using them to develop integrated transport systems in the future to prevent accidents.