Research Article

Smart Cities and Infrastructure: Managing Urban Scale Data for Predictive Maintenance and Resource Allocation

Authors

  • Manivannan Dhanasekaran AI/ML Engineering Leader, USA

Abstract

This article dives into how smart city technologies are changing urban areas, looking at how digital systems and physical infrastructure come together to create smarter, data-driven ways to manage cities. We'll explore architectural models for deploying urban sensors, techniques for gathering data, and how edge computing is being used, all while showcasing successful large-scale sensing projects. The discussion also covers computational methods for processing huge urban datasets, using machine learning to spot patterns in infrastructure, and the combined power of real-time and historical data analysis. You'll learn about predictive maintenance for public utilities, intelligent traffic control, how emergency services can be allocated dynamically, and the pros and cons of being proactive versus reactive with maintenance. Finally, we'll wrap up by looking at new urban sensing technologies, the challenges of integrating them with older systems, efforts to standardize for better interoperability, and the ethical concerns that come with widespread urban monitoring.

Article information

Journal

Journal of Computer Science and Technology Studies

Volume (Issue)

7 (7)

Pages

987-996

Published

2025-07-23

How to Cite

Manivannan Dhanasekaran. (2025). Smart Cities and Infrastructure: Managing Urban Scale Data for Predictive Maintenance and Resource Allocation. Journal of Computer Science and Technology Studies, 7(7), 987-996. https://doi.org/10.32996/jcsts.2025.7.7.110

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Keywords:

Smart infrastructure, urban transformation, predictive maintenance, edge computing, real-time analytics, machine learning applications, digital governance, pervasive monitoring, interoperability, internet of things, iot