Intelligent Traffic Management and Crime Scene Detection Using 5G Cameras

EasyChair Preprint 14678

Abstract

Urban traffic congestion is a critical challenge faced by cities globally, leading to significant delays, fuel wastage, and increased environmental pollution. Traditional traffic control systems, which rely on fixed signal timings, often fail to accommodate fluctuating traffic density, especially during peak hours. The project "Traffic Management Using Density" addresses this issue by developing an intelligent traffic management system that dynamically adjusts traffic lights based on real-time vehicle density. This approach aims to reduce congestion and optimize traffic flow at intersections, prioritizing roads with higher vehicle counts to minimize travel time and improve overall efficiency. The integration of 5G technology with advanced image processing algorithms forms the core of this system. High-speed 5G cameras are deployed at intersections to monitor vehicle density and detect emergency vehicles. The system processes this data in real time, enabling rapid adjustments to traffic signals. For instance, when an ambulance is detected, the system prioritizes the corresponding road by granting it a green light, ensuring faster and safer passage. Additionally, the project incorporates urban security measures by leveraging 5G cameras equipped with object recognition algorithms to detect criminal activity, such as theft or the presence of weapons. When suspicious activities are identified, the system alerts traffic monitoring offices and law enforcement, providing visual evidence to enhance public safety. Through these dual functionalities, the project not only improves traffic management but also contributes to urban security, making it a valuable asset for modern cities.

Keyphrases: 5G Technology Integration, Crime Detection System, Intelligent Traffic Management, Prioritization, Public SafetyEnhancement., Real-time Traffic Control, Vehicle Density Monitoring, emergency vehicle, urban traffic congestion

@booklet{EasyChair:14678,
  author    = {B Leelavathi and M Dakshayini},
  title     = {Intelligent Traffic Management and Crime Scene Detection Using 5G Cameras},
  howpublished = {EasyChair Preprint 14678},
  year      = {EasyChair, 2024}}