A Systematic Review of AI and IoT-Powered Smart Maintenance Methods in Industrial Application Domains

Authors

  • Suroor M. Albattat College of Engineering, Al-Iraqi University, Saba'a Abkar Complex, Baghdad, Iraq
  • Baraa M. Albaker College of Engineering, Al-Iraqi University, Saba'a Abkar Complex, Baghdad, Iraq
  • Malik A. Alsaedi College of Engineering, Al-Iraqi University, Saba'a Abkar Complex, Baghdad, Iraq
Volume: 15 | Issue: 5 | Pages: 26890-26900 | October 2025 | https://doi.org/10.48084/etasr.12455

Received: 2 June 2025 | Revised: 3 July 2025, 13 July 2025, and 17 July 2025 | Accepted: 20 July 2025 | Online: 6 October 2025


Corresponding author: Suroor M. Albattat

Abstract

In light of the rapid development of industrial systems within the era of the Fourth Industrial Revolution, predictive maintenance (PdM) has undergone a significant transformation through the integration of Artificial Intelligence (AI) enhancements with the Internet of Things (IoT), enabling real-time monitoring and accurate decision-making in industrial environments. This review provides a comprehensive analysis of 82 recent studies between 2019 and 2025, reviewing trends and developments, data integration, system compatibility, and real-time adaptability. Unlike previous reviews, this study presents a novel classification framework with clearer thematic distinctions by classifying the included studies into several industrial fields, such as smart factories, manufacturing, industrial equipment, machinery, and mobile robots, while identifying key research gaps and proposing future directions aligned with the Fourth Industrial Revolution.

Keywords:

Cyber-Physical Systems (CPS), Industry 4.0, Internet of things (IoT), smart manufacturing, Predictive Maintenance (PdM), Machine Learning (ML), Artificial Intelligence (AI)

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[1]
S. M. Albattat, B. M. Albaker, and M. A. Alsaedi, “A Systematic Review of AI and IoT-Powered Smart Maintenance Methods in Industrial Application Domains”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 5, pp. 26890–26900, Oct. 2025.

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