Article ID: | iaor2017505 |
Volume: | 32 |
Issue: | 2 |
Start Page Number: | 107 |
End Page Number: | 123 |
Publication Date: | Feb 2017 |
Journal: | Computer-Aided Civil and Infrastructure Engineering |
Authors: | Teizer J, Vela P A, Bgler M, Borrmann A, Ogunmakin G |
Keywords: | datamining, production, decision |
The high complexity of modern large‐scale construction projects leads their schedules to be sensitive to delays. At underground construction sites, the earthwork processes are vital, as most of the following tasks depend on them. This article presents a method for estimating the productivity of soil removal by combining two technologies based on computer vision: photogrammetry and video analysis. Photogrammetry is applied to create a time series of point clouds throughout excavation, which are used to measure the volume of the excavated soil for daily estimates of productivity. Video analysis is used to generate statistics regarding the construction activities for estimating productivity at finer time scales, when combined with the output from the photogrammetry pipeline. As there may be multiple causes for specific productivity levels, the automated generation of progress and activity statistics from both measurement methods supports interpretation of the productivity estimates. Comparison to annotated ground truth for the tracking and activity monitoring method highlights the reliability of the extracted information. The suitability of the approach is demonstrated by two case studies of real‐world urban excavation projects.