Automated Construction Progress and Quality Monitoring for Commercial Buildings with Unmanned Aerial Systems: An Application Study from Switzerland

Kielhauser, Clemens; Renteria Manzano, Raul; Hoffman, Jeffrey J.; Adey, Bryan T. (2020). Automated Construction Progress and Quality Monitoring for Commercial Buildings with Unmanned Aerial Systems: An Application Study from Switzerland Infrastructures, 5(11), p. 98. MDPI AG 10.3390/infrastructures5110098

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<p>Unmanned Aerial Systems (UASs), which have become a key tool in remote sensing in recent years, have also rapidly entered the practice of Architecture, Engineering, Construction, and Operations (AECO). This paper presents an application study of a methodology for monitoring construction progress and quality using real-time data from a commercial building during the execution phase and the results of an analysis of the costs and benefits of monitoring construction progress and quality with and without a UAS. The methodology used consists of three parts: (1) automated data collection at the construction site, (2) data processing, in which the collected data are processed to generate the outputs necessary for the data analysis, and (3) data analysis to monitor construction progress and quality. The method is based on the detection of structural elements, combined with four principles: the sectional approach, the calculation of the concrete volume, the height-distance measurement, and the detection of defects by visual comparisons. The cost-benefit analysis considers three cases: monitoring of progress (1) by the construction company using the UAS, (2) by external contractors using the UAS, and (3) by the construction company without using the UAS. We show that the in-house operation of the UAS is associated with medium costs. However, a return on investment can be achieved quickly if the strategy for the operation of the UAS is clearly defined. In summary, the use of a UAS for the automated monitoring of the construction progress and quality of commercial buildings is practicable, which can quickly lead to a return on investment. We also show that there is great potential for further improvements.</p>

Item Type:	Journal Article (Original Article)
Division/Institute:	School of Architecture, Wood and Civil Engineering School of Architecture, Wood and Civil Engineering > Institute for Urban Development and Infrastructure School of Architecture, Wood and Civil Engineering > Institute for Urban Development and Infrastructure > Transport Infrastructure
Name:	Kielhauser, Clemens0000-0003-1385-9909; Renteria Manzano, Raul; Hoffman, Jeffrey J. and Adey, Bryan T.
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TH Building construction
Publisher:	MDPI AG
Language:	English
Submitter:	Clemens Kielhauser
Date Deposited:	11 Aug 2021 09:27
Last Modified:	11 Aug 2021 09:27
Publisher DOI:	10.3390/infrastructures5110098
Additional Information:	Date: 2020
Uncontrolled Keywords:	BIM Point cloud Progress monitoring Quality monitoring
ARBOR DOI:	10.24451/arbor.14613
URI:	https://arbor.bfh.ch/id/eprint/14613