Abstract

As urbanization intensifies globally, nations are increasingly adopting the smart city approach to address the challenges of rising infrastructure demands and sustainability issues. Smart cities, powered by the Internet of Things (IoT), are designed to tackle these challenges by enabling real-time monitoring, digitization, and optimization of urban services. Nonetheless, the centralized cloud computing model often utilized by smart cities has challenges of high latency, bandwidth limitations, and privacy concerns. These challenges have resulted in the consideration of edge computing as the best option, as it enables the processing of data closer to its sources, rather than transferring to centralized platform. This makes decision-making faster while also enhancing security and enabling system resilience.
This article explores the important role of edge computing in IoT-driven smart city development across the globe, evaluating the effectiveness of edge computing in key domains such as smart transportation, energy management, public safety, and waste and water services. The article includes real-world case studies like Barcelona, New York, and Tokyo, analyzing the practical benefits, including reduced congestion, faster grid outage detection, and network traffic optimization the cities have gained from adopting the technology. It also presents the critical challenges such as interoperability, cybersecurity, infrastructure costs, and policy gaps, that are hindering faster adoption.