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Article

Drift Invariant Metric Quality Control of Construction Sites Using BIM and Point Cloud Data

Department of Civil Engineering, Geomatics Section, KU Leuven—Faculty of Engineering Technology, 9000 Ghent, Belgium
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Authors to whom correspondence should be addressed.
All authors contributed equally to this work.
ISPRS Int. J. Geo-Inf. 2020, 9(9), 545; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090545
Received: 24 July 2020 / Revised: 31 August 2020 / Accepted: 7 September 2020 / Published: 14 September 2020
(This article belongs to the Special Issue 3D Indoor Mapping and Modelling)
Construction site monitoring is currently performed through visual inspections and costly selective measurements. Due to the small overhead in construction projects, additional resources are scarce to frequently conduct a metric quality assessment of the constructed objects. However, contradictory, construction projects are characterised by high failure costs which are often caused by erroneously constructed structural objects. With the upcoming use of periodic remote sensing during the different phases of the building process, new possibilities arise to advance from a selective quality analysis to an in-depth assessment of the full construction site. In this work, a novel methodology is presented to rapidly evaluate a large number of built objects on a construction site. Given a point cloud and a set of as-design BIM elements, our method evaluates the deviations between both datasets and computes the positioning errors of each object. Unlike the current state of the art, our method computes the error vectors regardless of drift, noise, clutter and (geo)referencing errors, leading to a better detection rate. The main contributions are the efficient matching of both datasets, the drift invariant metric evaluation and the intuitive visualisation of the results. The proposed analysis facilitates the identification of construction errors early on in the process, hence significantly lowering the failure costs. The application is embedded in native BIM software and visualises the objects by a simple color code, providing an intuitive indicator for the positioning accuracy of the built objects. View Full-Text
Keywords: building information modeling; quality control; construction site; point cloud building information modeling; quality control; construction site; point cloud
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MDPI and ACS Style

Bassier, M.; Vincke, S.; De Winter, H.; Vergauwen, M. Drift Invariant Metric Quality Control of Construction Sites Using BIM and Point Cloud Data. ISPRS Int. J. Geo-Inf. 2020, 9, 545. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090545

AMA Style

Bassier M, Vincke S, De Winter H, Vergauwen M. Drift Invariant Metric Quality Control of Construction Sites Using BIM and Point Cloud Data. ISPRS International Journal of Geo-Information. 2020; 9(9):545. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090545

Chicago/Turabian Style

Bassier, Maarten, Stan Vincke, Heinder De Winter, and Maarten Vergauwen. 2020. "Drift Invariant Metric Quality Control of Construction Sites Using BIM and Point Cloud Data" ISPRS International Journal of Geo-Information 9, no. 9: 545. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090545

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