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Augmented Reality to Enable Users to Identify Deviations for Model Reconciliation

Autor(en):

ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 2, v. 11
Seite(n): 77
DOI: 10.3390/buildings11020077
Abstrakt:

Effective use of Building Information Modeling (BIM) during operation typically requires modeled content to accurately match the built spaces, which necessitates effective field verification techniques to ensure that BIM content matches the actual built conditions. Some contractors leverage laser scanning and other reality-capture technologies to verify modeled content prior to turnover, but these approaches can be time- and resource-intensive. Augmented reality (AR) enables users to view BIM content overlaid on their field of view of the built space. Research suggests potential for using AR for tasks related to field verification, but a study that systematically explores the specific types of deviations that can be detected with this technology is missing from the current literature. This paper tasks participants with using immersive AR to identify deviations from BIM in a ceiling plenum space that includes installed Mechanical, Electrical and Plumbing (MEP) components, which would typically be included in a coordinated BIM. The results suggest that AR can enable users to effectively identify large deviations and missing building elements. However, the results do not indicate that AR effectively enables users to identify small deviations and can potentially lead to identifying false positive observations, where accurately constructed elements are perceived as deviating from BIM. These results suggest that immersive AR can effectively be used to check whether recently built elements conform to the intended BIM in instances where speed of verification is more important than adhering to strict tolerances. For instances where accuracy (less than two inches) is critical, the results of this work suggest that AR can be used to help determine where in the building more accurate, but more resource-intensive, reality-capture technologies should be used.

Copyright: © 2021 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10578650
  • Veröffentlicht am:
    02.03.2021
  • Geändert am:
    02.06.2021
 
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