Edge Intelligence for Smart Cities and Intelligent Transportation Systems

Abstract

The rapid growth of urbanization and vehicular traffic has necessitated the deployment of intelligent systems to manage city resources efficiently. Edge Intelligence (EI), which combines edge computing with artificial intelligence (AI), provides a promising solution to handle the large-scale data generated by smart city infrastructure and intelligent transportation systems (ITS). By processing data closer to the source, EI reduces latency, enhances real-time decision-making, and optimizes resource usage. This review paper presents an overview of EI applications in smart cities and ITS, examines enabling technologies, discusses challenges, and identifies future research directions. The paper also highlights practical implementations and compares edge-based approaches with traditional cloud-centric models.

KEYWORDS: Edge Intelligence, Smart Cities, Intelligent Transportation Systems, Internet of Things, Low-Latency Computing, Real-Time Analytics