International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Real-Time Video Analysis for Intelligent Traffic Management, Public Safety, and Security: A Deep Learning Approach

Author(s) Mayank, Omkar Dixit, Anurag Vats, Dr. B . Lakshmi Dhevi
Country India
Abstract This paper proposes a novel centralized traffic management system designed to enhance road safety and streamline law enforcement. The system leverages a network of intelligent sensors and cameras to achieve real-time accident detection, traffic violation identification, and facial recognition. Data collected from these sensors is fed into a centralized hub for processing and analysis. Upon identifying an incident, the system promptly dispatches notifications to patrolling units, enabling faster response times for accidents and violations. Additionally, facial recognition capabilities allow for real-time identification of individuals, potentially aiding in apprehending criminals or locating missing persons. This paper will discuss the system architecture, core functionalities, and potential benefits for improved traffic management and public safety. We will also address the challenges associated with data privacy and security in such a centralized system.
Keywords Traffic Management System, Accident Detection, Traffic Violation Detection, Facial Recognition, Centralized System, Public Safety
Field Computer Applications
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-15
Cite This Real-Time Video Analysis for Intelligent Traffic Management, Public Safety, and Security: A Deep Learning Approach - Mayank, Omkar Dixit, Anurag Vats, Dr. B . Lakshmi Dhevi - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.17209
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.17209
Short DOI https://doi.org/gtq3dp
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