IoT and Predictive Analytics: Revolutionizing Utility Asset Management

This comprehensive article examines the transformative impact of Internet of Things (IoT) and predictive analytics integration on asset performance management within the utility industry. It explores how these technologies enable utilities to transition from reactive maintenance paradigms to proactive, data-driven approaches that significantly enhance operational efficiency and asset longevity. The article progresses through four key domains: the foundational sensor networks and data acquisition systems that enable continuous monitoring; the predictive analytics methodologies that transform raw data into actionable intelligence; the advanced digital twin technologies that create virtual replicas for simulation and optimization; and the quantifiable operational benefits realized through implementation. By synthesizing findings from multiple research studies across various utility sectors, the article provides a comprehensive framework for understanding how IoT and predictive analytics convergence are fundamentally reshaping maintenance practices, improving reliability metrics, extending asset lifespans, optimizing resource allocation, and enhancing regulatory compliance across water, electricity, and gas utilities.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-19
DOI
https://doi.org/10.5281/zenodo.17162212
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

IoT and Predictive Analytics: Revolutionizing Utility Asset Management

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

IoT and Predictive Analytics: Revolutionizing Utility Asset Management

article en

Abstract

This comprehensive article examines the transformative impact of Internet of Things (IoT) and predictive analytics integration on asset performance management within the utility industry. It explores how these technologies enable utilities to transition from reactive maintenance paradigms to proactive, data-driven approaches that significantly enhance operational efficiency and asset longevity. The article progresses through four key domains: the foundational sensor networks and data acquisition systems that enable continuous monitoring; the predictive analytics methodologies that transform raw data into actionable intelligence; the advanced digital twin technologies that create virtual replicas for simulation and optimization; and the quantifiable operational benefits realized through implementation. By synthesizing findings from multiple research studies across various utility sectors, the article provides a comprehensive framework for understanding how IoT and predictive analytics convergence are fundamentally reshaping maintenance practices, improving reliability metrics, extending asset lifespans, optimizing resource allocation, and enhancing regulatory compliance across water, electricity, and gas utilities.

Zenodo (CERN European Organization for Nuclear Research)
Film Independent (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Geochemistry and Geologic Mapping
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