AI-Powered Real-Time Anomaly Detection in Edge Computing Systems for Smart Cities (International Journal of Engineering and Computer Science, 2025)
Smart city technologies have become essential in today’s world as people experience the improvement of city infrastructure that increases effectiveness, contacts and ecological unfriendliness. However, the implementation of different technologies and developing data-intensive systems in smart cities creates various questions especially the system availability and security in real-time systems. This means that like in other complex systems, there are always different types of anomalous events including equipment malfunctions, inadequate data, or cyber security threats that hinder standard and expected operations that make the detection of such anomalies important.This paper explores how AI can help in real-time anomalies detection in edge computing systems, designed for smart cities. Edge computing in which data is processed nearer to the origin curtails general latency and provides improved response time, making it an excellent model for smart city implementation. The deep learning, clustering algorithms and federated learning enabled edge systems require accuracies greater than 90% in real-time to detect these anomalies for critical systems to run.Some of the problems and issues as presented in the paper include limited resources of edge devices, data privacy issues and reliability issues in deploying AI on edge systems. It also discusses the topic of energy-efficient frameworks for AI, the capability of utilizing next-gen AI for better interpretability known as Explainable AI (XAI), and the fusion of edge-to-cloud systems for addressing the dilemma of centralized as well as decentralized data processing.Lastly, the paper establishes how intelligent systems applied within smart city environments such as smart traffic management, energy grid monitoring, public safety, and environmental management provide theoretical and practical pathways to implementing AI-powered anomaly detection. The results put emphasis on the synergy between artificial intelligence and edge computing and show how it could help cities become more sustainable, smart, safe, and resourceful. This research endeavors to present the existing prospects and issues to help plan the further advancement and development of the literature in this field.