IoT, Big Data, Blockchain and Machine Learning Besides Its Transmutation with Modern Technological Applications

Abstract

Amid the augmentation of the Internet of Things (IoT), applications have become smarter and coupled devices give escalation to their exploitation in all facets of a modern city. As the capacity of the collected data increases, Machine Learning (ML) methods are applied to auxiliary boosting of intelligence and the abilities of an application. The field of smart transportation has fascinated many researchers and it has been accosted with both ML and IoT techniques. In this evaluation, smart transportation is contemplated to be a canopy term that conceals the route optimization, accident prevention/detection, parking, street lights, road anomalies, and infrastructure applications. The purpose of this document is to make a self-contained evaluation of ML techniques and IoT applications in Intelligent Transportation Systems (ITS) and attain a clear view of the developments in the above-mentioned fields and spot possible coverage musts. From the reviewed articles it becomes insightful that there is a possible lack of ML coverage for the Smart Lighting Systems and Smart Parking applications. Additionally, route optimization, parking, and accident/detection tend to be the most popular ITS applications among researchers, henceforth there is a huge possibility in implementing the IoT with real world applications with the support of various Big data concepts and Machine learning algorithms along with Block chain technology.