Real-time evacuating routing during earthquake using a sensor network in an indoor environment
Bibliographic record
Abstract
In this paper, we propose a framework for speeding the evacuation time of occupants in a building during an earthquake. The framework is based on the information collected from a sensor network, an algorithm to calculate evacuation routes, and dissemination of route information to occupants. The sensor network is used to determine the state of whether areas and spaces are transitable or blocked. State information is then used to calculate evacuation routes. We evaluate the performance of the proposed framework under the event of an earthquake by estimating the time in which an occupant is able to evacuate the building. Our results show that evacuation paths are sensitive to small blocking probabilities, which represent the intensity of earthquake damage of an indoor area in this paper. We also show that the information provided by a fully functional information network adopting the proposed framework simplifies the evacuation to the extent that an occupant experiences little or no confusion as to where to exit. In general, we see that an occupant may easily be routed to the exit to which evacuation may take the shortest time and that changes of evacuation routes may hardly occur. We show that the variations on evacuation times are small.
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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) | 0.000 | 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 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".