Abstract
On-site progress monitoring is essential for keeping track of the ongoing work on construction sites. Currently, this task is a manual, time-consuming activity. BIM-based progress monitoring facilitates the automated comparison of the actual state of construction with the planned state for the early detection of deviations in the construction process. In this chapter, we discuss an approach where the actual state of the construction site is captured using photogrammetric surveys. From these recordings, dense point clouds are generated by the fusion of disparity maps created with semi-global-matching (SGM). These are matched against the target state provided by a 4D Building Information Model. For matching the point cloud and the model, the distances between individual points of the cloud and a component’s surface are aggregated using a regular cell grid. For each cell, the degree of coverage is determined. Based on this, a confidence value is computed which serves as a basis for detecting the existence of a respective component. Additionally, process- and dependency-relations provided by the BIM model are taken into account to further enhance the detection process.
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Braun, A., Tuttas, S., Stilla, U., Borrmann, A. (2018). BIM-Based Progress Monitoring. In: Borrmann, A., König, M., Koch, C., Beetz, J. (eds) Building Information Modeling. Springer, Cham. https://doi.org/10.1007/978-3-319-92862-3_28
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DOI: https://doi.org/10.1007/978-3-319-92862-3_28
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