Edge Computing in Smart Cities: Transforming Urban Infrastructure through Decentralized Processing

Abstract

Rapid urbanization has necessitated sophisticated computational paradigms capable of addressing complex challenges inherent in contemporary metropolitan environments. Edge computing emerges as a transformative technology, fundamentally altering how cities process data and manage critical infrastructure systems through distributed computational frameworks positioned at data generation points. Unlike traditional cloud-based systems relying on remote data centers, edge computing brings processing power directly into urban environments, enabling instantaneous responses to dynamic conditions while reducing dependency on centralized resources. Integration of edge computing into smart city infrastructure creates interconnected networks of distributed processing nodes, facilitating real-time traffic optimization, environmental monitoring, public safety enhancement, and resource management across multiple urban domains. Advanced implementations demonstrate substantial improvements in transportation network efficiency through autonomous traffic signal control, air quality monitoring via distributed sensor networks, and enhanced surveillance through localized video analytics processing. Edge computing additionally enables unprecedented optimization of energy distribution networks, water quality monitoring systems, and waste collection operations through intelligent resource allocation and predictive maintenance capabilities. Despite significant advantages, deployment faces considerable challenges, including security vulnerabilities in distributed systems, interoperability complexities across heterogeneous platforms, and regulatory compliance requirements spanning multiple jurisdictions.