The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLVIII-2/W1-2022
08 Dec 2022
 | 08 Dec 2022


A. H. Qureshi, W. S. Alaloul, A. Murtiyoso, S. J. Hussain, S. Saad, and V. K. Oad

Keywords: Photogrammetry, Point Cloud, Point Cloud Evaluation, Steel Reinforcement, Progress Detection

Abstract. The construction industry practices and processes are evolving constantly, and with the emergence of Industry 4.0, the use of technologies is expanding. Construction progress monitoring is an essential project lifecycle process; project success and timely completion are linked with effective progress monitoring operations and adopted tools. In the domain of automated construction progress monitoring, 3D modeling techniques have been studied a lot, with laser scanning and photogrammetry as two main methods. Although laser scanning provides precise and detailed 3D models, it is an expensive technology. Moreover, the literature reveals that for digitized construction progress monitoring, the major focus has been given to primary reinforced concrete (RC) structures compared to rebar. In contrast, rebar is a key element in RC structures, as structural integrity is dependent on steel reinforcement design, which makes rebar monitoring an essential activity. This study aimed to devise an automated monitoring digital-based methodology for effective and efficient onsite rebar monitoring considering quantitative parameters e.g., rebar length and rebar spacing. The developed module successfully interpreted photogrammetry-based 3D point cloud rebar model for the aforementioned parameters with an overall achieved accuracy ≥ 98%.