ABSTRACT
The Internet of Things (IoT) and Machine Learning (ML), better transportation applications, and connected gadgets have made these technologies widely applicable in many sectors of society. To increase the intelligence and capacity of the transportation system, IoT and ML technologies are applied. Routing protocol, parking, road lamps, accident prevention/detection, road imperfections, and infrastructure applications are all part of the transportation system. The goal of this chapter is to describe ML and Internet of Things (IoT) applications in Transportation Systems (TS), as well as to provide a comprehensive vision of such fields’ development and spot possible coverage gaps. In this chapter, we present the Adaptive Enhanced K-Nearest Neighbor algorithm (AEKNN), which is based on ML, to improve Advanced Lighting and Advanced Parking applications in TS. A hybrid fuzzy cuckoo optimization algorithm (HFCOA) is suggested to enhance the performance of the transportation system. The planned IoT and ML-based transportation system would enhance travel time, reduce pauses, and waits at intersections, safeguard public health, control and increase speed, and handle incidents.
