EDGE COMPUTING ARCHITECTURES FOR REAL-TIME SMART CITY APPLICATIONS

Abstract

Smart cities rely on vast networks of sensors and IoT devices to support real-time applications such as intelligent traffic systems, public safety, environmental monitoring, and emergency response. Traditional cloud-centric architectures often fail to meet stringent latency, bandwidth, and reliability demands due to centralized data processing and long communication paths. Edge computing introduces a decentralized architecture that brings computation closer to data sources, enabling real-time analytics, reduced latency, improved bandwidth utilization, and enhanced resilience. This paper reviews edge computing architectures tailored for smart city applications, analyzes key components and frameworks, evaluates performance benefits through case studies, and identifies future research directions. Findings indicate that multi-tier edge architectures significantly improve system responsiveness and support mission-critical smart city services.