Point Cloud-Based Smart Building Acceptance System for Surface Quality Evaluation

The current expansion of building structures has created a demand for efficient and smart surface quality evaluation at the acceptance phase. However, the conventional approach mainly relies on manual work, which is labor-intensive, time-consuming, and unrepeatable. This study presents a systematic...

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Bibliographic Details
Published inBuildings (Basel) Vol. 13; no. 11; p. 2893
Main Authors Cai, Dongbo, Chai, Shaoqiang, Wei, Mingzhuan, Wu, Hui, Shen, Nan, Zhou, Yin, Ding, Yanchao, Hu, Kaixin, Hu, Xingyi
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2023
Subjects
Acceptance
Accuracy
Aesthetics
Algorithms
Analysis
Automation
building acceptance
Building components
Concrete
Construction contracts
Construction costs
Efficiency
Geometry
Image segmentation
Information flow
Information management
Lasers
point cloud
Quality assessment
Surface properties
surface quality evaluation (SQE)
surface segmentation
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Summary:The current expansion of building structures has created a demand for efficient and smart surface quality evaluation at the acceptance phase. However, the conventional approach mainly relies on manual work, which is labor-intensive, time-consuming, and unrepeatable. This study presents a systematic and practical solution for surface quality evaluation of indoor building elements during the acceptance phase using point cloud. The practical indoor scanning parameters determination procedure was proposed by analyzing the project requirements, room environment, and apparatus. An improved DBSCAN algorithm was developed by introducing a plane validation and coplanar checking to facilitate the surface segmentation from the point cloud. And a revised Least Median of Square-based algorithm was proposed to identify the best-fit plane. Afterwards, the flatness, verticality, and squareness were evaluated and depicted using a color-coded map based on the segmented point cloud. The experiment on an apartment showcases how the system improves the information flow and accuracy during building acceptance, resulting in a potentially smart acceptance activity.
ISSN:2075-5309
2075-5309
DOI:10.3390/buildings13112893