Utilizing Deep Learning For Dynamic Video Analysis In Traffic Control, Safety, And Security

Abstract

This paper introduces an innovative centralized traffic management system aimed at enhancing road safety and optimizing law enforcement procedures. The system harnesses a network of smart sensors and cameras to achieve instant detection of accidents, identification of traffic violations, and facial recognition. Information gathered by these sensors is transmitted to a central hub for analysis and processing. Once an incident is detected, the system promptly alerts patrolling units, leading to quicker response times for addressing accidents and violations. Furthermore, facial recognition technology enables real-time identification of individu- als, potentially aiding in the apprehension of criminals or locating missing persons. The paper will delve into the system’s architecture, key functionalities, and potential advantages for improving traffic management and public safety. It will also discuss the challenges related to data privacy and security inherent in such a centralized system.