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August 5, 2025Journal of Engineering Research and ReportsOpen Access

A Machine Learning Framework for Predictive Maintenance in Smart Facilities Using IoT Sensor Data

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Authors

SMShamsudeen MusaThe Federal Polytechnic, Ado-EkitiJAJ. O. AbassThe Federal Polytechnic, Ado-EkitiBOB. N. ObajuFederal Polytechnic Ede

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Implication

The proposed framework demonstrates improved predictive maintenance in smart facilities using IoT data, indicating enhanced efficiency and reduced downtime.

Key Points

  • The framework integrates machine learning techniques for predictive maintenance, showcasing its applicability in smart facilities.
  • LSTM outperformed other models with an F1-score of 0.89, indicating high predictive accuracy for maintenance tasks.
  • Implementation led to a 40% reduction in maintenance response time and a 47% decrease in unplanned downtime.
  • Successful integration with existing CMMS platforms highlights the framework's practical application in real-world scenarios.

Cite This Study

Musa et al. (2025) studied this question.

synapsesocial.com/papers/689522009f4f1c896c42907dhttps://doi.org/10.9734/jerr/2025/v27i81601
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