Vision-Based Progress Monitoring of Building Structures Using Point-Intensity Approach

Progress quantification of construction projects is critical for project managers to manage projects effectively. The trade-off between computation time and accuracy is a key aspect while selecting the quantification method. Though accuracy is essential, project managers require real-time information about quantities of work completed on various building components to make timely decisions. Several researchers have developed individual pipelines using vision-based technologies for automated progress quantification. However, they face significant implementation challenges, including higher computational complexity, skilled personals, and costly equipment. Hence, this study aims to define an easy-to-implement pipeline to quantify the holistic progress and element-wise progress of a building. For executing this, the method utilizes point intensity as a fundamental parameter. The progress of a specified element is calculated by comparing the number of points in the as-built model and the number of anticipated points from the as-designed model of the same point intensities. The method directly integrates the as-designed BIM model with the scan data through a user-friendly visual programming tool - Grasshopper3D for progress quantification. The workflow provides one-click progress report generation with minimal inputs from the users for basic alignment of the imported as-built data. As the point clouds are directly addressed as a single entity, and to-be intensity has been calculated through an intensity-based randomized approach, the method utilizes less computation for the whole process.