Main Article Content
Internet of Things (IoT) and its applications have grown to be smarter and connected various devices which give rise to its utilization in all aspect of a modern city. As the amount of the composed data increases, the Machine Learning (ML) method is usefully to the further development in the various intelligence and potential of the application. Smart transportation based application has concerned various researchers as well as it has been approach by means of both ML techniques and IoT methods. This article gives an importance to smart transportation which is measured to be an umbrella term which covers optimization of routes, the parking, accident detection / prevention, street lights, road anomalies, and the infrastructure based applications. The intention of this paper is to construct a self-contained evaluation of IoT based applications with Machine Learning techniques in Intelligent based Transportation Systems (ITS) and attain a clear examination of the tendency in the aforementioned fields, and to spot the possible coverage needs. From the reviews done, it becomes thoughtful that there is a probably lack of Machine Language coverage for the Smart Lighting based Systems and Smart Parking based applications. In addition, the route optimization, accident/detection and parking, be likely to be the majority popular Intelligent Transportation Systems (ITS) based applications among the researchers for better business intelligence (BI) and development.