Dynamic Traffic Light Monitoring System

Abstract

The growing population trend has always been an alarming issue as it results in a constant need to modify our systems and the working orders need to be changed drastically to meet the common demands. One of the major problem faced by the citizens is of Congestion. The present implementations of ITS in the country, in several cities, are focused primarily on the traffic volume calculation rather than informing the public. The proposed idea will significantly reduce human involvement as the data uploaded to cloud will be computed without any human inputs. The connected network will be using neural networks that significantly reduce the risk of network failure, keeping the system updated at all instances. The fault tolerance will be improved by re-routing the network through additional subsidiary nodes present to channel the data in case of a failure. Updation of data and manipulations to the server will be dynamic, data flowing through algorithms and the public only able to see the simplified computed data. Our proposition uses technologies that are used currently in traffic systems but takes them a step further as they use both software (through codes) and hardware (through sensors) components to provide an almost error free management system.