A cloud-based integration of Building Information Modeling and Virtual Reality through game engine to facilitate the design of Age-in-Place homes at the conceptual stage
Bibliographic record
Abstract
While the Canadian population ages, designers are encountering new challenges that significantly affect the design of new houses. This demographic shift will impose major changes in the demand for housing toward more adaptable and specialized homes that require designers to develop new strategic design solutions. Presently, the main challenge to designers when creating age-in-place houses is lacking the knowledge about the requirements of that type of homes. Therefore, this study describes the development of a Semi-automated computer model that offers designers and users a unique opportunity to do real-time simulation in an interactive environment while enhancing the communication and interaction between owners and designers to meet inhabitants' needs by reducing future modifications and alterations of houses to age in them. The said model is a cloud-based integration between BIM, Universal Design (UD), Age-in-Place (AIP) design requirements, and Virtual Reality (VR) that allows owners to be engaged in the design process at the early stage to achieve efficient outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".