Auto‐calibration of Hall effect sensors for home energy consumption monitoring
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Bibliographic record
Abstract
A technique to improve the accuracy of an electrical energy consumption monitoring system is proposed. This system is based on a network of Hall effect wireless sensors attached to the wire at the output of every circuit breaker in the electrical distribution panel. The readings provided by the Hall effect sensors show significant gain errors due to their sensitivity to the distance between the sensor and the monitored wire. To mitigate these gain errors and increase the system accuracy, the addition of a single high‐precision current transformer sensor at the main electrical input is proposed, measuring the total current. This signal is used as the reference signal in a least‐mean square algorithm to compensate for the unknown gains of the Hall effect sensors. Experimental results using three prototype Hall effect sensors show that the proposed solution converges within 1.7 min, reducing the average current measurement error from 2.54 to 0.46 A rms .
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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) | 0.000 | 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