BIM/Digital Twin-Based Construction Progress Monitoring through Reality Capture to Extended Reality (DRX)
Bibliographic record
Abstract
A generic framework for automated construction progress monitoring via introducing a new integration method incorporating the use of reality capture technologies (Laser Scanner and Wireless Sensors), Building Information Modeling (BIM), Digital Twin (DT), and Extended Reality (XR) has been developed in this study. The proposed framework, BIM/Digital twin-based reality capture to extended reality (DRX), in this research, arrays steps on how these technologies work collaboratively to create, capture, generate, analyze, manage, and visualize construction progress data, information, and reports. Interactions among steps and processes to be followed for implementation purposes are discussed through process modeling and Integrated Function Modeling (IDEF0) language. Finally, the reliability, validity, and contribution of the proposed framework was evaluated to understand the DRX model's effectiveness when implemented in real practice. The empirical data were collected through a computerized self-administered questionnaire (CSAQ) survey conducted on contracting and engineering consulting companies operating in the USA, UAE, Sweden, Denmark, and Canada. The structural equation modeling (SEM) method was used to test the hypotheses and develop the skill model. Then, the strengths and challenges of the DRX model have been described based on three different sources of academic publications, construction professionals’ experiences, and the author's lessons learned. It is concluded how the technologies of Unmanned Aerial Vehicles (UAV), reality capturing, visualization, and robotics, with construction management principles, can establish a DRX model to enable accurate and real-time progress monitoring of complex projects. DRX facilitates more precise as-planned creation, faster as-built data acquisition, optimizing the whole created and captured data, and\npresenting them in a real environment. This study provides a roadmap for future efforts involving implementation of the DRX system as a new era of design, construction, and monitoring to empower clients, project managers, designers, and other stockholders with advanced decision-making mechanisms to solve discrepancies in an effective manner.\nKeywords: Automated Construction Progress Monitoring, Building Information Modeling (BIM), Reality Capture (RC), Digital Twins (DT), Extended Reality (XR).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".