AI-Powered Digital Twins for Predictive Infrastructure Management

  • Authors

    • P. K. Iyengar Scientific Computing Researcher, BARC, India Author

    DOI:

    https://doi.org/10.67228/30715628/IJMIET-2025PII4R8P

    Published 07-03-2025

  • Artificial Intelligence, Digital Twin, Predictive Infrastructure Management, Machine Learning, Internet of Things, Predictive Maintenance, Smart Cities, Infrastructure Analytics, Deep Learning, Intelligent Asset Management

    Issue

    Vol. 8 No. 2 (2025)

    Section

    Articles

    How to Cite

    [1]
    P. K. Iyengar, “AI-Powered Digital Twins for Predictive Infrastructure Management”, ijmiet, vol. 8, no. 2, pp. 01–15, Jul. 2025, doi: 10.67228/30715628/IJMIET-2025PII4R8P.

  • Abstract

    Smart infrastructure increasingly requires predictive maintenance to improve asset reliability and reduce operational risks. AI-powered Digital Twins integrate IoT, cloud computing, big data, and machine learning to enable real-time monitoring, anomaly detection, asset health assessment, and failure prediction. This paper reviews their architecture, enabling technologies, applications, current research trends, and key challenges, including data quality, interoperability, cybersecurity, and explainability. The study highlights that AI-driven Digital Twins significantly improve maintenance efficiency, reduce costs, enhance safety, and support sustainable, intelligent infrastructure management.

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