Machine Learning for Internet of Things-Based Smart Transportation Networks

Abstract

The world's population is expanding, and people want to live in cities, making city administration a difficult task. Traditional cities, with their shared characteristics, will be unable to provide human demands. Machine learning (ML) techniques are being used to increase an application's understanding and capabilities as the volume of data received rises. Smart transportation is defined as an umbrella concept that describes route optimization, parking, street lighting, and infrastructure applications in this evaluation. The purpose of this research is to present a self-contained assessment of machine learning techniques and internet of things applications in intelligent transportation to provide a clear picture of the current state of circumstances. In this chapter, the authors attempt to explain several features of smart transportation in greater depth.