Skip to the content

Automating progress measurement of construction projects

Zhang, X, Bakis, N, Lukins, T, Ibrahim, Y, Wu, S, Kagioglou, M, Aouad, G, Kaka, A and Trucco, E 2009, 'Automating progress measurement of construction projects' , Automation in Construction, 18 (3) , pp. 294-301.

[img] PDF - Published Version
Restricted to Repository staff only

Download (1MB) | Request a copy


The accurate and up to date measurement of work in progress on construction sites is vital for project management functions like schedule and cost control. Currently, it takes place using traditional building surveying techniques and visual inspections. The usually monthly measurements are error prone and not frequent enough for reliable and effective project controls. This paper explores the potential of using computer vision technology in assisting the project management task. In particular, it examines the development of an integrated building information system that aims to determine the progress of construction from digital images captured on site in order to semi-automate the work in progress measurement and calculation of interim payments as well as function as an early warning system of potential delays. The study focuses on the quantity rather than quality aspect of work and is limited to the superstructure of buildings.

Item Type: Article
Themes: Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science > QA076 Computer software
Subjects / Themes > T Technology > TA Engineering (General). Civil engineering (General)
Built and Human Environment
Subjects outside of the University Themes
Schools: Colleges and Schools > College of Science & Technology
Colleges and Schools > College of Science & Technology > School of the Built Environment
Colleges and Schools > College of Science & Technology > School of the Built Environment > Salford Centre for Research & Innovation (SCRI)
Journal or Publication Title: Automation in Construction
Publisher: Elsevier
Refereed: Yes
ISSN: 0926-5805
Depositing User: Dr Nick Bakis
Date Deposited: 16 Mar 2011 10:37
Last Modified: 19 Aug 2014 11:59
References: [1] K.S. Saidi, A.M. Lytle, W.C. Stone, Report of the NIST workshop on data exchange standards at the construction job site, Proc. of 20th International Symposium on Automation and Robotics in Construction (ISARC), 2003, pp. 617–622. [2] I.N. Davidson, M.J. Skibniewshi, Simulation of automated data collection in buildings, Journal of Computing in Civil Engineering 9 (1) (1995) 9–20. [3] R. Navon, “Research in automated measurement of project performance indicators”, Automation in Construction 16 (2) (2007) 176–188. [4] M. Tsai, J. Yang, C. Lin, Synchronization-based model for improving on-site data collection performance, Automation in Construction 16 (3) (2007) 323–335. [5] R. Navon, R. Sacks, Assessing research issues in Automated Project Performance Control (APPC), Automation in Construction 16 (4) (2007) 474–484. [6] J.N. Abeid, D. Arditi, Time-lapse digital photography applied to project management, Journal of Construction Engineering and Management 128 (6) (2002) 530–535. [7] L.G. Shapiro, G.C. Stockman, Computer Vision, Prentice Hall, 2001. [8] R. Fisher, K. Dawson-Howe, A. Fitzgibbon, C. Robertson, E. Trucco, Dictionary of Computer Vision and Image Processing, Wiley, 2005. [9] A.R. Dick, P.H.S. Torr, R. Cipolla, Modelling and interpretation of architecture from several images, International Journal of Computer Vision, 60 (2) (2004) 111–134. [10] H. Cantzler, R.B. Fisher, M. Devy, Improving architectural 3D reconstruction by plane and edge constraining, Proc. of British Machine Vision Association Conference, Cardiff, UK, 2002, pp. 43–52. [11] T. Werner, F. Schaffalitzky, A. Zisserman, Automated architecture reconstruction from close-range photogrammetry, the Proc. of CIPA International Symposium: Surveying and Documentation of Historic Buildings, Monuments, Sites, Traditional and Modern Methods, Potsdam, Germany, 2001. [12] A. Huertas, R. Nevatia, Detecting changes in aerial views of man-made structures, Image and Vision Computing, 18 (8) (2000) 583–596. [13] C. Gordon, F. Boukamp, D. Huber, E. Latimer, K. Park, B. Akinci, Combining reality capture technologies for construction defect detection: a case study, Proc. of 9th EuropIA International Conference (EIA9), Istanbul, Turkey, 2003, pp. 99–108. [14] E. Trucco,A.P. Kaka, A framework for automatic progress assessment on construction sites using computer vision, International Journal of IT in Architecture, Engineering and Construction 2 (2) (2004) 147–164. [15] X. Zhang, N. Bakis, S. Wu, M. Kagioglou, G. Aouad, T. Lukins, Y. Ibrahim, Incorporating the progress measurement dimension to an integrated building information system: a research framework, Proc. of CIB w78 conference, 2007. [16] B. Vries, J. Harink, “Generation of a construction planning from a 3D CAD model”, Automation in Construction 16 (1) (2007) 13–18. [17] K.W. Chau, M. Anson, J.P. Zhang, 4D dynamic construction management and visualization software: 1. Development, Automation in Construction 14 (4) (2005) 512–524. [18] Kathleen McKinney, Martin Fischer, Generating, evaluating and visualizing construction schedules with CAD tools, Automation in Construction 7 (6) (1998) 433–447. [19] R. Sacks, A.Warszawski, A project model for an automated building system: design and planning phases, Automation in Construction 7 (1) (1997) 21–34. [20] N. Bakis, X. Zhang, S.Wu,M. Kagioglou,G.Aouad, An initial assessment to automating cost and schedule control based on the progress of construction captured using computer vision and photogrammetry techniques, SCRI Symposium, 2007. [21] O. Abudayyeh,W. Rasdorf, Prototype integrated cost and schedule control system, Journal of Computing in Civil Engineering 7 (2) (1993) 181–198. [22] R. Carr, Cost, schedule and time variances and integration, Journal of Construction Engineering and Management 119 (2) (1993) 245–265. [23] PMI, A guide to the project management body of knowledge, PMI Standards Committee, 1996. [24] Y. Jung, S.Woo, Flexible work breakdownstructure for integrated cost and schedule control, Journal of Construction Engineering and Management 130 (5) (2004) 616–625. [25] C. Hendrickson, Project Management for Construction, Prentice Hall, 1998. [26] T. Lukins, Y. Ibrahim, A. Kaka, E. Trucco, Now you see it: the case for measuring progress with computer vision, SCRI Symposium, 2007. [27] Y. Ibrahim, E. Trucco, A. Kaka, M. Kagioglou, G. Aouad, Semi-automatic development of the work breakdown structure for construction projects, SCRI Symposium, 2007. [28] Y. Jung, S. Kang, Knowledge-based standard progress measurement for integrated cost and schedule performance control, Journal of Construction Engineering and Management 133 (1) (2007) 10–21.

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)


Downloads per month over past year