Elastic cloud–IoT architecture for smart city traffic management: Performance, energy efficiency, and real-time analytics

Authors

https://doi.org/10.22105/sci.v2i2.37

Abstract

Rapid urbanization and increasing vehicle population have led to severe traffic congestion and pollution in modern cities. Smart city initiatives leverage Internet of Things (IoT) technology to address these challenges and optimize traffic management systems. This paper explores the role of cloud computing in enhancing IoT-based traffic management by providing scalable data processing, real-time analytics, and intelligent decision-making capabilities. Cloud platforms enable seamless integration of distributed IoT devices, such as sensors and cameras, that collect traffic data. Using cloud-based machine-learning models, this system can predict traffic patterns, manage congestion, and improve road safety. The paper also discusses the benefits, challenges, and potential solutions for implementing cloud-enabled traffic management in smart cities, emphasizing improved efficiency, reduced costs, and enhanced sustainability.

Keywords:

Cloud computing, Internet of things, Real-time analysis, Urban mobility, Machine learning

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Published

2025-06-23

Issue

Vol. 2 No. 2 (2025): Smart City Insights

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How to Cite

Karimi, H., & Goudarzi Karim, R. (2025). Elastic cloud–IoT architecture for smart city traffic management: Performance, energy efficiency, and real-time analytics. Smart City Insights, 2(2), 88-98. https://doi.org/10.22105/sci.v2i2.37

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