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https://hdl.handle.net/10356/173344
Title: | As-built BIM reconstruction of piping systems using smartphone videogrammetry and terrestrial laser scanning | Authors: | Xie, Yuan Teo, Mou Xuan Li, Siyi Huang, Lihui Liang, Nanying Cai, Yiyu |
Keywords: | Engineering::Mechanical engineering | Issue Date: | 2023 | Source: | Xie, Y., Teo, M. X., Li, S., Huang, L., Liang, N. & Cai, Y. (2023). As-built BIM reconstruction of piping systems using smartphone videogrammetry and terrestrial laser scanning. Automation in Construction, 156, 105120-. https://dx.doi.org/10.1016/j.autcon.2023.105120 | Journal: | Automation in Construction | Abstract: | The increasing adoption of Building Information Modeling (BIM) in the construction industry has created a demand for methods to update existing facilities with accurate as-built BIM models. While terrestrial laser scanners (TLS) are commonly used for indoor surveys due to their speed and precision, they face limitations in areas with physical constraints like confined spaces and occlusions, with pipes being particularly affected. This paper presents a smartphone videogrammetry approach designed to enhance the accuracy and completeness of terrestrial laser scanner (TLS) point clouds for as-built BIM reconstruction. The method involves capturing missing areas within the TLS point cloud with smartphones and then seamlessly integrating these data into a more comprehensive multi-modal point cloud. This approach is validated using real scan data and offers convenience through the use of readily available and cost-effective smartphones, while its iterative nature facilitates progressive BIM reconstruction of pipe structures. Additionally, a compatible progressive BIM reconstruction framework is outlined, aiming to modernize scan-to-BIM practices in the construction industry, with a case study demonstrating its feasibility. | URI: | https://hdl.handle.net/10356/173344 | ISSN: | 0926-5805 | DOI: | 10.1016/j.autcon.2023.105120 | Schools: | School of Mechanical and Aerospace Engineering | Research Centres: | Surbana Jurong-NTU Corporate Lab | Rights: | © 2023 Elsevier B.V. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | MAE Journal Articles |
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