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A Systematic Review of Artificial Intelligence Applied to Facility Management in the Building Information Modeling Context and Future Research Directions

Author(s): ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 11, v. 12
Page(s): 1939
DOI: 10.3390/buildings12111939
Abstract:

Throughout the operation and maintenance (O&M) stage, facility management (FM) teams collect and process data from different sources, often needing to be adequately considered when making future decisions. This data could feed statistical models based on artificial intelligence (AI), thus improving decision-making in FM. Building information modeling (BIM) appears in this context, leveraging how data and information are systematized, enabling structured information and its use. This article addresses the state-of-the-art of using AI techniques applied to FM in the BIM context, analyzing articles between 2012 and 2021 related to this area. It is interesting to note that only from 2018 onwards, there is a substantial increase in these publications, from about 8 publications (2012 to 2017) to 24 publications (2018 to 2021) on average. This growth shows the progressive application of the optimization methods mentioned above, which opens new opportunities for the FM profession. This study contributes to the body of knowledge by highlighting the investigated tendency and gaps in critical areas and their relationship with the research topic. Noteworthy future directions are suggested, directing on (i) data and system integration; (ii) predictive models; (iii) automatic as-built/classification; (iv) internet of things; (v) energy management; and (vi) augmented/virtual reality.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10700287
  • Published on:
    10/12/2022
  • Last updated on:
    15/02/2023
 
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