Population explosions have led to an unprecedented increase in the number of objects and vehicles on the road. As a result, the traffic volume is so heavy that traffic accidents are increasing. This document monitors traffic flows using a computer vision paradigm in which images or image sequences provide an enhancement to street vision. This study uses the Raspberry Pi's camera module and Raspberry Pi 3 to detect vehicles and monitor and estimate traffic flow with low-cost electronics. It also aims to develop remote access using the Raspberry Pi to detect only vehicles and track and count anomalies. It occurs in the monitored area. The proposed system captures a video stream such as a vehicle in a surveillance area, computes the information, and sends a compressed video stream to provide a video-based solution implemented in OpenCV primarily by Python programming. To do. The proposed method is considered an economical solution for the industry to develop cost-effective traffic management solutions.
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Component List
- raspberry pi
- Webcam
- Power supply
- wires and jumper
Features
- detects the vehicle, its speed and take the count of vehicles over the highway
