Emirates Scholar Research Center - Research Publishing & Indexing Center

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

Authors:  Varun Reja

Journal: 38th International Symposium On Automation And Robotics In Construction Dubai, UAE.

Publication Date:  Nov 2021.

Keywords: Automated Progress Monitoring Point-Intensity Scan-Vs-BIM Progress Quantification Visual Programming Single-Click Report Generation BIM-Based Tracking Point Clouds Automation In Construction Management


Abstract

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.

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