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|a 10.1109/TVCG.2023.3320223
|2 doi
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|a eng
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1 |
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|a Sermarini, John
|e verfasserin
|4 aut
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|a Investigating the Impact of Augmented Reality and BIM on Retrofitting Training for Non-Experts
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|c 2023
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|a Text
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|a ƒaComputermedien
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|a Date Revised 06.11.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Augmented Reality (AR) tools have shown significant potential in providing on-site visualization of Building Information Modeling (BIM) data and models for supporting construction evaluation, inspection, and guidance. Retrofitting existing buildings, however, remains a challenging task requiring more innovative solutions to successfully integrate AR and BIM. This study aims to investigate the impact of AR+BIM technology on the retrofitting training process and assess the potential for future on-site usage. We conducted a study with 64 non-expert participants, who were asked to perform a common retrofitting procedure of an electrical outlet installation using either an AR+BIM system or a standard printed blueprint documentation set. Our findings indicate that AR+BIM reduced task time significantly and improved performance consistency across participants, while also decreasing the physical and cognitive demands of the training. This study provides a foundation for augmenting future retrofitting construction research that can extend the use of [Formula: see text] technology, thus facilitating more efficient retrofitting of existing buildings. A video presentation of this article and all supplemental materials are available at https://github.com/DesignLabUCF/SENSEable_RetrofittingTraining
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|a Journal Article
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|a Michlowitz, Robert A
|e verfasserin
|4 aut
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| 700 |
1 |
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|a LaViola, Joseph J
|e verfasserin
|4 aut
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| 700 |
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|a Walters, Lori C
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Azevedo, Roger
|e verfasserin
|4 aut
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|a Kider, Joseph T
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 29(2023), 11 vom: 03. Nov., Seite 4655-4665
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|g number:11
|g day:03
|g month:11
|g pages:4655-4665
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|u http://dx.doi.org/10.1109/TVCG.2023.3320223
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