Abstract
Effective progress control is vital for steering infrastructure construction to completion with minimum delay. Walking through the infrastructure project site to record progress in different activities is time-consuming, requiring information extracted from construction drawings, schedules, and budgets, as well as data collected from the construction site. This process can be automated by using advanced remote sensing technologies. This study contributes to progress monitoring in large horizontal infrastructure projects. It presents a practical automated method using laser scanning technology that can track the project’s progress in a real construction environment with limited human input. It is robust and accurate and is currently operational. The system capitalizes on the success of laboratory experiments. This system deals with occlusions effectively, accelerates the registration process of multiple scans, reduces the noise in the data, recognizes the objects of irregular shape, and is economically feasible. It provides evidence that all current challenges encountered in using laser scanners in monitoring construction progress can be overcome. This method has been successfully tested in the Wacker Drive reconstruction project in Chicago, IL.
Highlights
Effective monitoring of the progress of infrastructure construction is a key function of construction management as the information obtained is critical in evaluating periodic payment requests submitted by the contractor [1]
This paper is an attempt to monitor construction progress in real-life large infrastructure projects by making sure the barriers normally encountered in progress control are overcome, i.e., objects are identified using the objects’ 3D coordinates, reliable point cloud data are captured despite occlusions, and the status of a project is compared at different times using the objects’ shape definition and geometry information while allowing for tolerances
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Summary
Effective monitoring of the progress of infrastructure construction is a key function of construction management as the information obtained is critical in evaluating periodic payment requests submitted by the contractor [1]. This paper is an attempt to monitor construction progress in real-life large infrastructure projects by making sure the barriers normally encountered in progress control are overcome, i.e., objects are identified using the objects’ 3D coordinates, reliable point cloud data are captured despite occlusions, and the status of a project is compared at different times using the objects’ shape definition and geometry information while allowing for tolerances. The objective of this study is to develop an advanced progress measurement method that automates these processes in monitoring progress in horizontal construction projects. It modifies the method developed by Zhang and Arditi [20] in laboratory conditions. Infrastructures 2020, 5, 83 information, the objects’ 3D coordinates are acquired, and equations are developed to calculate the volume/surface area of the objects involved in each activity
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