Daylighting Control and Simulation for LED-Based Energy-Efficient Lighting Systems
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
This paper presents a simulation environment and daylighting control strategy to achieve energy-efficient lighting while providing desired lighting levels at the target points. The lighting strategy is based on a self-tuning multivariable controller, which maintains the illuminance levels at user-defined set-points while improving the energy consumption due to artificial lighting. The simulation environment utilizes the so-called layered lighting design, which allows one to evaluate the performance of different control strategies. Furthermore, the environment can be used to validate the performance of a lighting control strategy, in quasi-real-time, and assess its potential energy savings. The above approach has not been investigated in prior literature and may thus be of interest in energy-aware automated lighting systems. A case study is presented for an open-plan office space exposed to variable natural light through windows and a set of individually addressable light emitting diode luminaries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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