Literature Review on AI and IoT Used in Smart Transportation

Abstract

The System integration of the Internet of Things (IoT) and Artificial Intelligence (AI) have become a vital component of the modern urban planning, transforming traditional transportation systems into intelligent, connected and increasingly autonomous networks. This technological convergence offers promising solutions to persistent urban challenges such as traffic congestion, road accidents and air pollution.

This paper presents an extensive review of existing literature on the use of AI and IoT across four key areas: pollution management, smart parking systems, intelligent navigation and driver safety enhancement. It critically examines conventional system architectures, explores data-driven models and evaluates AI-based methods that enable real-time decision-making. Furthermore, the study outlines the major IoT sensors and communication technologies employed within these systems.

The paper also discusses scalability and performance aspects in real-world applications, highlighting the balance between system efficiency, public safety and environmental sustainability. Important considerations such as data privacy, interoperability, processing delays, and regulatory challenges are examined in detail. Finally, the review identifies significant future research opportunities, including edge computing, Vehicle-to-Everything (V2X) communication, federated learning and 5G/6G-enabled services. These advancements are expected to guide researchers and policymakers toward building safer, smarter and more sustainable transportation ecosystems.