Optimal Personal Comfort Management Using SPOT+
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
We present SPOT+, a system that allows office workers to optimally balance between heating energy consumption and personal thermal comfort. In prior work, we described SPOT: a smart personal thermal control system based on reactive control [8]. In contrast, the SPOT+ system performs predictive control. Specifically, SPOT+ uses the k-nearest-neighbour algorithm to predict room occupancy and learning-based model predictive control (LBMPC) to predict future room temperature and to compute the optimal sequence of control inputs. This allows the system to schedule future temperature setpoints to optimize an objective function expressed as a linear combination of thermal comfort and energy consumption. We have deployed SPOT+ as well as four other alternative control schemes in an office workspace. We find that SPOT+ reduces energy usage by 60% compared to a fixed-temperature setpoint and reduces personal thermal discomfort from 0.36 to 0.02 (in the ASHRAE comfort scale) compared to SPOT.
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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 | 0.000 |
| 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) | 0.001 | 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