Automated Schedule and Progress Updating of IFC-Based 4D BIMs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Researchers have studied the detection of actual site conditions and the state of construction progress using various field data capture technologies. To fully exploit these solutions, a method was developed to automatically update industry foundation classes (IFC) based four-dimensional (4D) building information models (BIM) in terms of schedule and progress. To automatically incorporate progress data into 4D BIMs, the method modifies the schedule hierarchy; updates progress ratios for the building elements; color codes the building elements based on their actual and expected progress; and updates the task durations and finish dates. A real case application is provided to demonstrate the potential of the system. The method’s reliance on nonproprietary IFC data format, its high accuracy rates, and its real-time performance in real-life testing scenarios provide promise to the future of automated 4D BIM updating and its use during construction. Input data can come from any source, thereby leveraging the use of reality capture technologies for BIM-based progress tracking.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it