Journal of Structural and Construction Engineering

Journal of Structural and Construction Engineering

A framework for automated progress monitoring of concrete building projects based on computer vision and building information modeling

Document Type : Original Article

Authors
1 MSc, Faculty of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 Assistant Professor, Faculty of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran
3 Assistant Professor, Faculty of Computer Engineering, K. N. Toosi University of Technology, Tehran, Iran
Abstract
Construction progress monitoring is a critical aspect of project management, playing a decisive role in improving productivity, controlling costs, and shortening the overall schedule. Accurate and timely progress tracking enables better, more informed decisions and helps prevent problems and delays. Traditional progress monitoring methods, however, are largely manual and time-consuming, suffering from high costs and a dependence on specialized labor and advanced equipment. This study develops a novel automated construction progress monitoring framework by combining computer-vision techniques with Building Information Modeling (BIM). The framework employs image processing to detect and localize concrete columns, while BIM data provides the planned-status reference against which actual progress is measured. Once the columns are identified, the number of completed stories—and thus overall project progress—is computed from the analyzed images. Case studies demonstrate that the proposed method achieves high accuracy with minimal image input. Using only one photograph per façade, and without laser scanners or large image datasets, the framework can reliably quantify progress in concrete structures. These capabilities substantially reduce cost and improve the practicality and accessibility of automated monitoring, especially for small- and medium-sized projects. Overall, the presented approach constitutes an effective step toward accelerating, optimizing, and smartening project-management processes in civil engineering.
Keywords

Subjects


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  • Receive Date 21 May 2025
  • Revise Date 04 September 2025
  • Accept Date 27 September 2025