Automated progress control using laser scanning technology Chengyi Zhang a , David Arditi b, ⁎ a Dynasty Group Inc., 205 West Wacker Drive, Suite 1450, Chicago, IL 60606, United States b Department of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology, Chicago, IL 60616, United States abstract article info Article history: Accepted 14 August 2013 Available online 17 September 2013 Keywords: Construction scheduling Progress control Laser scanning Assessing progress in construction activities is time consuming and requires the use of specialized personnel. Au- tomated progress control could reduce the workforce, the cost, and the time used, reduce disagreements, and add to the overall efficiency of project management. Attempts have been made in the past to resolve this issue using image processing and other techniques but the results have not been satisfactory. A new attempt is now made to set up a system that can assess progress control with minimum human input. An experiment makes use of laser scanning technology. The initial results appear to be promising but there are still obstacles to surmount. The sys- tem is robust and accurate in laboratory conditions and constitutes proof of concept. Improvements are necessary to accelerate the registration process of multiple scans, to recognize objects of irregular shape, and to assess the practicality and economic feasibility of such a system. © 2013 Elsevier B.V. All rights reserved. 1. Introduction Construction progress control is a critical task in project manage- ment. Traditionally, construction managers walk around in the con- struction site to verify progress in different activities and understand the current status of the project. Current progress control is time con- suming, requiring data collection and extraction from construction drawings, schedules, and budget information [35]. The quality of prog- ress control depends on the quality of the inspector's field reports, which may sometimes contain entry mistakes. The quality of manually collected and extracted progress data is typically low [18]. Over the years, attempts have been made to streamline this process by using ad- vanced computer technologies. For example, Abeid and Arditi [4] devel- oped an automated real-time monitoring system that links time-lapse digital movies of construction activities, the critical path method (CPM), and visual progress control techniques. It enables managers at the contractor's and the owner's headquarters to follow developments at the construction site in real time. Zhang et al. [34] explored the poten- tial of using computer vision technology in assisting project managers with determining the progress of construction from digital images cap- tured on the site. The study focused on the quantity rather than the quality of the work and was limited to the superstructure of buildings. Gordon et al. [21] presented the details of an automated planning ap- proach to support on-site construction inspections and thereby allow inspectors to both generate complete, detailed inspection plans and to consider numerous possible alternatives in detail. Several researchers experimented with different imaging tech- niques to produce essential construction management information in an effective manner. For example, Abeid et al. [7] developed a method for recognizing the presence of a structural component in a digital picture taken at a construction site through the component's color and position. Abdel-Qader et al. [2] compared diverse image processing techniques and chose a series of techniques that work best for the iden- tification of cracks in a bridge component. By combining image process- ing techniques and a database of construction materials, Brilakis and Soibelman [13] used a shape retrieval mechanism to recognize a range of construction material resources. They also used 3D imaging tech- niques to analyze construction project processes. Quinones-Rozo et al. [25] applied image processing techniques to quantify excavation prog- ress. Golparvar-Fard et al. [18,19] proposed automated methods for progress monitoring using photographs taken from a construction site. Tang et al. [29], surveyed techniques developed in civil engineering and computer science that can be utilized to automate the process of creating as-built BIMs. Gong and Caldas [20] developed and eval- uated several vision-based construction object recognition and tracking methods for construction video analysis. Walia and Teizer [32] simulat- ed the processing of location data for collision detection and proximity analysis and demonstrated that real-time proximity detection of re- sources is feasible. Most research on automated project progress control aims to measure the physical quantities in-place by using spatial sensing technologies [30]. However, these methods are mostly based on immature technologies, are cumbersome to use, and require frequent and constant manual interven- tion. Methods need to be developed that are not only easy to use, but are also based on mature technologies that have proved to be of value in day-to-day construction operations, such as laser scanning. Automation in Construction 36 (2013) 108–116 ⁎ Corresponding author at: Department of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology, Chicago, IL 60616, United States. E-mail addresses: czhang@dynastygrp.com (C. Zhang), arditi@iit.edu (D. Arditi). 0926-5805/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.autcon.2013.08.012 Contents lists available at ScienceDirect Automation in Construction journal homepage: www.elsevier.com/locate/autcon