Intelligent Based Real Time Traffic Monitoring in Smart Cities

Abstract

PC-based Intelligent Traffic Monitoring System is unable to deal with the on-going issues surrounding congestion. The current traffic light models are not suited to tackle problems such as traffic jams, ease of access for emergency vehicles and prevention of accidents. In order to counteract these issues, we propose ‘PC-based Intelligent Traffic Monitoring System with Real-time Analysis for Smart Cities’. The system consists of a network of cameras installed at strategic locations across the city, which capture images of vehicles and pedestrians. These images are then processed by intelligent algorithms, which analyse the data and provide real-time traffic information. The system is also equipped with a real-time monitoring interface, which displays the traffic data in an easy-to-understand format. The system is designed to help cities optimize their traffic flow and reduce congestion. By analysing real-time traffic data, city officials can make informed decisions about traffic management and can take immediate action to alleviate congestion. This project will focus on two aspects of implementation. First and foremost, to make traffic light controlling more efficient, image processing alongside with embedded system, will be used. This system will intelligently decide when to alternate signals based on the emergency vehicle on each lane which will increase road capacity and traffic flow. Secondly the system favours school students by giving green signal to give them free passage. It is a matter of concern, as emergency vehicles are being categorized as priority vehicles, so their waiting time should be minimum.

Research on optimization method for traffic signal control at intersections in smart cities based on adaptive artificial fish swarm algorithm

“…However, the control efficiency of this method for traffic intersection signal lights needs to be verified. Reference [ 14 ] puts forward an intelligent traffic monitoring system based on pc, which captures the images of vehicles and pedestrians, helps cities optimize traffic flow and reduce congestion. According to the emergency vehicles in each lane, intelligently decide when to change signals, thus increasing road capacity and traffic flow.…”