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Automated progress tracking using 4D schedule and 3D sensing technologies
Abstract
Abstract Efficient and effective construction progress tracking is critical to construction management. Current manual tracking methods are time consuming and/or error prone. Three dimensional (3D) laser scanners are being investigated in the construction industry and have shown potential for supporting progress tracking. However, their full potential has not yet been achieved. The reason may be that commercial software packages are still too complicated for processing scanned data. Methods have however been developed for the automated recognition of project 3D CAD model objects in site laser scans. A novel system is thus described herein that combines 3D object recognition technology with schedule information into a combined 4D object oriented progress tracking system. This system is tested on a comprehensive field database acquired during the construction of the Engineering V Building at the University of Waterloo. It demonstrates a degree of accuracy for automated progress tracking that meets or exceeds typical manual performance.
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Cited by
Computer vision techniques in construction: A critical review
Xu, S., Wang, J., Shou, W., Ngo, T., Sadick, A.-M., & Wang, X. (2021) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-020-09504-3 · Cited by 409
Automated construction progress measurement using a 4D building information model and 3D data
Kim, C., Son, H., & Kim, C. (2013) · Automation in Construction · doi:10.1016/j.autcon.2012.11.041 · Cited by 317
Dimitrov, A., & Golparvar-Fard, M. (2014) · Advanced Engineering Informatics · doi:10.1016/j.aei.2013.11.002 · Cited by 261
Computational methodologies for optimal sensor placement in structural health monitoring: A review
Tan, Y., & Zhang, L. (2020) · Structural Health Monitoring · doi:10.1177/1475921719877579 · Cited by 186
Cyber-physical systems integration of building information models and the physical construction
Akanmu, A., & Anumba, C. J. (2015) · Engineering, Construction and Architectural Management · doi:10.1108/ecam-07-2014-0097 · Cited by 122
Metadata
- Authors
- Turkan, Y., Bosche, F., Haas, C. T., & Haas, R.
- Venue
- Automation in Construction
- Publisher
- Elsevier BV
- Published
- 2012-03
- Volume
- 22
- Pages
- 414-421
- ISSN
- 0926-5805 (ISSN-L)
- OpenAlex
- W2057531282
- Cited by
- 374
- References
- 0
- FWCI
- 27.69
- Type
- journal article
- Language
- en
- Open access
- closed
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- Turkan, Y., Bosche, F., Haas, C. T., & Haas, R. (2012). Automated progress tracking using 4D schedule and 3D sensing technologies. Automation in Construction. https://doi.org/10.1016/j.autcon.2011.10.003
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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