Combining Reality Capture Technologies for Construction Defect Detection: A Case Study

† Abstract: Defects that occur during the construction process account for a large percentage of overall defects in the built environment. Defects waste time and money, and affect the overall performance of the built environment. These problems can be minimized with proactive application of advanced scanners, sensing, and data modelling techniques. Researchers in the departments of Architecture, Robotics, and Civil and Environmental Engineering at Carnegie Mellon University are investigating ways to integrate suites of emerging evaluation technologies to help find, record, manage, and limit the impact of construction defects. As part of this effort, the researchers have conducted a case study on a construction site near Pittsburgh, Pennsylvania. The case study serves to identify challenges in applying specific reality capture technologies and in coordinating suites of these tools on construction sites. The researchers conducted the following activities: creation of a 3D design model, generation of strategies and mechanisms to create 3D as-built models; establishment of specific measurement goals; creation of laser scanner and sensor planning software; targeted use of laser scanners and wireless embedded sensing for capturing as-built data; and analysis of captured data for possible defects. This paper discusses the process of deploying sensing and scanning tools on the case study construction site, and the process of implementing components of an integrated early defect detection system.