Review Paper on Automation of Traffic Signal Monitoring System using Machine Learning and Internet of Things (IoT)

Abstract

In the new advancing world, traffic rule infringement has become a focal issue for most of the creating nations. The quantity of vehicles is expanding quickly, just as the quantity of traffic rule infringement is expanding exponentially. Overseeing traffic rule infringement has consistently been a dull and bargaining task. Despite the fact that the procedure of traffic the board has gotten computerized, it is a difficult issue because of the fast increment in the populace, thus relate increment of their vehicles, and the assorted variety of the number plates additionally makes the errand progressively troublesome. The chief target of this paper is to control the traffic rule infringement precisely and cost-viably. The proposed model incorporates a computerized framework that utilizes closeness sensors and is camera-dependent on Arduino to catch video. The project presents automatic recognition of number plates of vehicles that mainly cross the pedestrian crossing. This should be possible utilizing AI methods and other image processing systems for plate confinement and character recognition, which makes it quicker and simpler to distinguish the number of plates. In the wake of perceiving the vehicle number from the number plate, the SMS based module is utilized to inform the vehicle proprietors about their traffic rule infringement. Through this paper, we can propose a financially savvy and increasingly effective programmed framework to decrease the number of mishaps that occur close to the pedestrian crossing.