Automated Traffic Control System Through Internet of Things

Abstract

Traffic is the most important part of everyone’s life. Thus it may be traffic to the blog or your website or the real-time traffic in the world. The traffic is the worst-case scenario for the people who are in urgency. The proposed system claims to be working in the smart city. Smart cities are driven by automated traffic control blocks and barricades. The system ensures clean and clear traffic within the sustainable area. The area should not be overcrowded nor should the vehicles be dormant. The important part of the system is to enhance the traffic mechanism and control the chaos without any deviation or progression. The most important part of the system is the controller among the four ways paved system, as the traffic and the other amenities will be in a pragmatic situation. So, to control the deviation and maintain a peaceful balance among the buzzing vehicles the controller and the artificial neural network play a predominant role. The controller is devised and deployed in the way to control and find the vehicles which don’t abide the traffic rules and regulations. A camera attached to the system captures the image of the number plate and identifies the owner of the vehicle and drops an immediate fine to the user of the vehicle. This is an instant behavior of the system. Thus all these happen within a fraction of a second. Thus according to the proposed model, the crime rate and the vehicle tress passing will be reduced and controlled. The proposed system helps in maintaining the collision between the vehicles and the control of the congestion of the unwanted vehicles. This will also promote an eco-friendly environment and reduce fuel consumption. It also prevents unwanted accidents in the traffic and the people who want to cross the road will be able to cross freely. They also provide point-to-point traffic congestion in different lanes and also provide data on the different vehicle speeds. The speed of the vehicle is calculated by the GPS which is fixed in every vehicle which in turn calculates the estimated speed of the vehicle which is in motion. They also provide control signals and transfer data to the other posts to stop the car that disobeyed by providing a barricade to the car in the next traffic pole. The traffic lights are trained through the neural networking methodology to adapt themselves to the buzzing traffic to optimize its time and change its light accordingly. The vamping technology is highly adopted in this system to control traffic on road.