Smart Cities and Machine Learning: Enabling Intelligent Urban Systems

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Ben Williams
Max Bannett

Abstract

The rapid urbanization of the 21st century has intensified the demand for smarter, more efficient, and sustainable urban environments. Smart cities, driven by data and automation, have emerged as a response to these challenges, with machine learning (ML) playing a pivotal role in their realization. ML techniques empower smart cities to analyze vast amounts of data, optimize urban infrastructure, improve resource utilization, and enhance the quality of life for citizens. This paper explores how ML is transforming urban ecosystems through intelligent traffic management, energy optimization, environmental monitoring, and predictive public services. It also discusses the challenges of data privacy, interoperability, and ethical considerations that must be addressed to achieve truly intelligent and equitable urban systems. The research concludes that machine learning, when integrated with IoT, cloud computing, and edge analytics, represents the cornerstone of sustainable and adaptive urban governance.

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How to Cite
Ben Williams, & Max Bannett. (2025). Smart Cities and Machine Learning: Enabling Intelligent Urban Systems . Pioneer Research Journal of Computing Science, 2(4), 1–6. Retrieved from https://prjcs.com/index.php/prjcs/article/view/106

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