In this innovative and automotive world everything is getting computerized. Beginning from home apparatuses to following to the industrial manufacturing, everything is going to be smart. Traffic control system is one of major problematic issues in all over the world. In conventional traffic control
Real time Traffic Monitoring and Smart Controlling System to Ensure Smooth Traffic Flow
In this innovative and automotive world everything is getting computerized. Beginning from home apparatuses to following to the industrial manufacturing, everything is going to be smart. Traffic control system is one of major problematic issues in all over the world. In conventional traffic control system every signal having fix time mostly 60 seconds on each of the road at a regular interval independent of traffic on a particular road, either the traffic is low or dense. This conventional traffic light control systems used everywhere in the world to monitor and control the flow of vehicles through the junctions of many roads. This Project idea also a step forward towards the smart city. In which the traffic is controlled by a microcontroller. The cameras are installed by which the working load of traffic wardens is shared. Our project is able to work on real time traffic monitoring and controlling using programming algorithms and reduce human working. This system also having synchronization of multiple traffic light systems at adjacent intersections and various parameters were involved. This system based on Raspberry pi microcontroller and based on three main functions. Controlling the flow of traffic, providing the path for emergency vehicles and also show the divergence plan when the traffic is high on any particular side of the road. The mutual interference between adjacent traffic light systems makes him smarter and leads to reduction in traffic jam and congestions. The system overcomes the major traffic issues and help ease in the vehicle flow. Moreover, a display device shows the congestion alert system on the previous junctions on the same road.
Our system use Raspberry-pi model 4 using OpenCV library. System is design to get images from webcam then detects the vehicle and count them using OpenCV background segmentation algorithms (Gaussians Segmenter). Each vehicle denotes by a segmented rectangular shape. By counting the vehicles the Raspberry-pi process further and compare the traffic density on all the roads and change the time laps for the roads with heavy traffic and low traffic. If there is heavy traffic on a road system is capable of showing a divergence plan on the previous traffic section.
The final deliverable form of our project will be a prorotype model consisting of Raspberry-pi model 4 interfaced with A4tech webcam for monitoring the traffic and control the traffic junction smartly by monitoring real time scenarios of traffic. LCD display also gives diversion alerts on the previous section in case heavy traffic on any junction. Light poles also present on the junction having colourful traffic lights. Power supply also connected to give supply to the whole hardware components.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspberry-pi model 4 | Equipment | 1 | 12850 | 12850 |
| Micro SD card 32GB | Equipment | 1 | 1650 | 1650 |
| A4Tech WebCam | Equipment | 4 | 4800 | 19200 |
| Relay Module | Equipment | 2 | 650 | 1300 |
| LED Light Bulb | Equipment | 24 | 60 | 1440 |
| Pi LCD 5 inch | Equipment | 1 | 8000 | 8000 |
| Hardware Base | Miscellaneous | 1 | 6000 | 6000 |
| Other Material and Tools | Miscellaneous | 1 | 2500 | 2500 |
| Connecting Wires | Miscellaneous | 2 | 260 | 520 |
| 5V DC Power Supply | Equipment | 1 | 780 | 780 |
| Raspberry-pi casing and Adapter | Equipment | 1 | 1100 | 1100 |
| Total in (Rs) | 55340 |
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