Traffic Resolution Algorithms, Machine Learning and Sensors

Abstract

Traffic detection software or applications already exist in the market today, be it embedded as a small aspect of a navigation app or a complete standalone individual platform but all of them have a sole purpose to detect the magnitude of traffic i.e. cars present in a particular area or a road. These technologies are also embedded many platforms which incorporate technologies like IoT and big data analytics which can determine the speed and location and even predict the many outcomes based on the heat signatures, fuel level, carriage etc. of many vehicles and help in live monitoring of such. Though all these technologies help in avoiding the traffic but no such technology can help in resolving the traffic once you are stuck in one. This paper talks about a proposition of a solution which by utilizing the present technologies in the market like mapping of traffic threshold and density analysis which works together with machine learning based algorithms and IoT enabled vehicles and passing instructions computed by the algorithm to each of the vehicles can help in achieving and resolving one of the most prominent problems faced by mankind today.