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BIM-FM integrated solution resourcing to digital techniques

  • S.I. : Visual Pattern Recognition and Extraction for Cultural Heritage
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Abstract

The facility management (FM) has been suffering significant changes since the introduction of building information modeling (BIM) in the Architecture, Engineering, Construction and Operation (AECO) sector. However, there are still challenges in BIM implementation during the building use phase, such as the difficulties related to the personalization of the maintenance management information for each case, and modeling the as-built conditions. Disclosing building data to all the stakeholders involved in the building life cycle is also a challenging task. So, this paper aims to present an integrated solution for BIM–FM to categorize and prioritize maintenance management, with the resource to digital techniques. For this purpose, the methodology developed consists of 1—the recognition and preparation of the site conditions; 2—Image collection using an Unmanned Aerial Vehicle (UAV); 3—Image processing and software comparison; 4—Obtaining point cloud and its integration in a BIM software; 5—3D building modeling in Revit software, 5—Damage detection through Photogrammetry Point Cloud, and 6—Placement of building anomalies by means of placeholders. This work allows exploring BIM–FM representation and data integration for building condition assessment and its representation in a collaborative tool. This methodology will enhance the usability of BIM methodology in FM since it allows the data update in the model, avoids the information loss or fragmentation of the building life cycle and gives access to BIM users and non-users.

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Data availability statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Acknowledgements

This research work was partially funded by the Portuguese Government through the FCT (Foundation for Science and Technology) and European Social Fund under the PhD grant SFRH/BD/147532/2019, awarded to the first author. This work was supported by the Foundation for Science and Technology (FCT)¢Aveiro Research Centre for Risks and Sustainability in Construction (RISCO), Universidade de Aveiro, Portugal [FCT/UIDB/ECI/04450/2020].

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  1. RISCO—Research Center for Risks and Sustainability in Construction, Department of Civil Engineering, University of Aveiro, 3810-193, Aveiro, Portugal

    Raquel Matos, Hugo Rodrigues, Aníbal Costa & Fernanda Rodrigues

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  1. Raquel Matos
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Correspondence to Raquel Matos.

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Matos, R., Rodrigues, H., Costa, A. et al. BIM-FM integrated solution resourcing to digital techniques. Neural Comput & Applic 36, 11833–11847 (2024). https://doi.org/10.1007/s00521-023-08907-0

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