Mixed Reality-based Digital Twinning of Building Circularity: A Co-Design Approach for Sustainable Buildings
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
Sustainability in construction practices is becoming the need of the day, and the construction sector is getting adoptive to the integration of digital tools to explore the opportunities for enhancing sustainability and circular economy applications, offering significant benefits to both industry and society.To achieve this goal, this article discusses a sustainability framework combining Digital Twin (DT), Mixed Reality (MR), and Life-Cycle Assessment (LCA) to align with circular economy principles in building construction.A case study of a single-family house in Kelowna, BC, Canada is conducted to demonstrate the potential of this integration for comprehensive LCA of buildings.The LCA analysis of the building is performed using OneClick LCA-an LCA platform.The results of LCA account for the embodied carbon, improved material circularity, life cycle cost efficiency, etc.A DT Dashboard (DTD) of the building's circularity model is also developed, which monitors and optimizes the whole life cycle of the building.The DTD is then deployed to MR hardware -Microsoft HoloLens for enabling onsite circularity analysis of the building.This not only allows for immersive visualization of LCA data but also enhances stakeholders' collaboration and decisionmaking.This way the study showcases how immersive DT can potentially be a game-changer for sustainable construction and provides an industrially replicable model.
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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 | 0.001 |
| 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