Automated Progress Tracking of Erection of Concrete Structures

One of the main criticisms of the construction industry is that projects are too often completed behind schedule (and/or with cost overruns). Schedule delays may result from poor planning, but also from poor progress control, because, if progress deviation is identified too late, then actions can often not be taken to avoid the impact of these delays on the overall project schedule. Progress tracking of erection of concrete structures in particular is a very demanding task requiring intensive data collection. It is because erection of concrete structures involves many steps like erection of scaffolding, formwork and rebar assemblies, concrete placement, and removal of scaffolding and formwork. Current manual tracking methods, mainly based on foremen daily reports, are typically time consuming and/or error prone. Improved progress tracking requires better project three dimensional (3D) as-built status tracking. Until recently, accurate and comprehensive 3D as-built status tracking remained impractical since the available technology made it too time and labour intensive. However, developments made in 3D imaging technologies, specifically laser scanning and photogrammetry, and 3D (even 4D) modeling in the last two decades make fast and accurate 3D as-built status tracking possible. Three dimensional (3D) Laser Scanners (LADARs) are capable of capturing and recording the 3D status of construction sites with high accuracy in short periods of time and have thus the potential to effectively support progress tracking. A system for automated progress tracking recently developed (Bosche, 2009) combines 4D modelling and laser scanning. Given a laser scan of a construction site and its acquisition date, the system quasi-automatically recognizes the building elements that are expected to be built at that date and visible in the scan. Results from multiple scans obtained on the same date but from different locations can be aggregated, and the combined recognition results are used to automatically infer site progress status, and consequently update the schedule. In this paper, this system is tested with real life data acquired over the course of construction of the new Engineering V Building at the University of Waterloo. Experimental results demonstrate the significant potential of this system.