The scope of this project is to overcome traffic congestion caused by ineffective traffic management systems that are outdated and work on a pre-defined countdown. These traditional systems allot timings irrespective of the actual density in traffic on a specific road thereby causing large red light
Smart Traffic Management System
The scope of this project is to overcome traffic congestion caused by ineffective traffic management systems that are outdated and work on a pre-defined countdown. These traditional systems allot timings irrespective of the actual density in traffic on a specific road thereby causing large red light delays. The system we propose ensures traffic lights respond to real time values of traffic, thereby allowing proper management of time and resources.
The main purpose of the smart traffic management system is to allot timings to a traffic signal based on the level of traffic on a lane. In order to calculate the level of traffic on each lane the road is divided into three equally spaced sections. Each section houses an ultrasonic sensor to determine if vehicles are present in that particular area. The ultrasonic determines the presence of an obstacle by finding the distance taken for a transmitted signal to be received.
In this project we intend to deliver that we first calculate the density of traffic which is determined using a combination of ultrasonic sensors and image processing techniques. This information is processed by a Raspberry Pi, which in turn controls the traffic light indicators. In addition to that, the data that is collected is sent to the cloud, and can be used to monitor traffic flow at periodic intervals. In case of sensor system failure, the values stored in the cloud will also be useful in predicting the density of traffic based on long term periodic analysis.
Our system is better then conventional systems as our system works on real time so it is not hindered by the change in traffic flow as the day goes by.
It reduces the time spent waiting for the signal.
It increases the traffic flow .
Our system also detects ambulance and close all other signals to let ambulance easily pass by. This way our project provides health benefits
In this project we intend to deliver that we first calculate the density of traffic which is determined using a combination of ultrasonic sensors and image processing techniques. This information is processed by a Raspberry Pi, which in turn controls the traffic light indicators. In addition to that, the data that is collected is sent to the cloud, and can be used to monitor traffic flow at periodic intervals. In case of sensor system failure, the values stored in the cloud will also be useful in predicting the density of traffic based on long term periodic analysis.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Camera Module | Equipment | 1 | 5000 | 5000 |
| Arduino UNO | Equipment | 1 | 1000 | 1000 |
| Vero board | Equipment | 1 | 50 | 50 |
| traffic modules | Equipment | 6 | 110 | 660 |
| Dc jack | Equipment | 1 | 30 | 30 |
| Wire connectors 4pin | Equipment | 10 | 40 | 400 |
| data cable arduino nano | Equipment | 1 | 150 | 150 |
| Total in (Rs) | 7290 |
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