Visible Light Communication Based Indoor Positioning Techniques
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
Positioning technique has become an indispensable part of our daily lives. Compared with the well-solved positioning issue in outdoor areas, indoor positioning is still far from being well explored, and existing techniques in this area are still far from being sufficiently mature to be widely used in practice. Recently, visible light communication based indoor positioning, also referred to as visible light based positioning, has attracted great attention and much work has been carried out, which reveals remarkable positioning accuracy. In this article, we provide a comprehensive survey of visible light based positioning. We first introduce some fundamental issues in visible light based positioning and further categorize existing systems in this field according to different design criteria. We then give a comprehensive survey of state-of-the-art systems, and introduce how each of the systems works and discuss their merits and deficiencies. Finally, we discuss challenging issues in this area and also point out future directions.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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