Automated construction progress monitoring of buildings through mobile mapping and as-built modeling

The traditional construction progress–monitoring approach is manual, time-consuming, and inaccurate, leading to time and cost overruns in construction projects. Automated progress-monitoring approaches are used to collect construction progress information accurately to address these issues. The automated methods utilize state-of-the-art technology, such as cameras and laser scanners, in conjunction with 3D building information modeling (BIM) to monitor the progress of the work. The outputs of the laser scanners and cameras are often point clouds containing noise and redundant elements that require removal. Consequently, the automated approach is associated with noise and redundant elements in the input data. Therefore, the problems of mitigating noise, extracting objects of interest from the point cloud, and achieving accurate and detailed measurements of progress require scrutiny. This thesis presents a novel construction progress–monitoring approach that measures work progress as a percentage. The study integrates a mobile scanner utilizing a simultaneous localization and mapping technique with an as-built BIM model to gather quick and accurate construction site–progress information. Additionally, the method utilizes the Hausdorff distance to filter out noise and extract objects of interest from a point cloud collected at construction sites. In this study, the as-built BIM model of the site is generated based on the result of the Hausdorff distance. This model is then compared with the as-designed BIM model of the project to obtain detailed and accurate progress information as a percentage. Additionally, this methodology has the potential to determine the discrepancy between the intended design and the as-built model, quantify construction waste in the construction phase, and indicate the cost-overrun status of the project based on material usage. The obtained progress information is expressed as a percentage and is used to update the construction schedule, material procurement, and decision-making processes. Further, the generated as-built BIM model serves as a 3D BIM record of the project for future maintenance and renovation. The model developed in this study was assessed across various scenarios in real construction projects in different Australian suburbs. The construction projects included masonry construction, timber-framed construction, and sheeting tasks to verify the methodology's applicability and practicality. The findings from these diverse scenarios show that the method can obtain detailed and accurate progress information with an accuracy rate of 94.67, 92.74, and 96.57 percent, respectively. Additionally, the method effectively filters out noise and redundant elements from the point cloud and quantifies construction waste in the construction phase through the utilization of the as-built BIM model.