Wi-Fi-based Positioning in a Complex Underground Environment
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
Underground mining tunnels constitute a very particular environment for radio wave propagation – with characteristics of both indoor and outdoor “regular” environments. This paper shows how a general-purpose Wi- Fi-based indoor positioning system, OwlPS (Owl Positioning System) was adapted to work in that particular environment. A series of experiments, conducted in a formerly exploited gold mine at 70 metres below the surface, across about 400 metres of drifts, is then introduced; it primarily aims at determining the positioning accuracy that can be reached in such a context with a Wi-Fi-based positioning system using the signal strength at 2.4 GHz. The results obtained are improved with a filter, and the mean Euclidean distance error is under 10 metres in most cases when the terminal is carried by an operator; this makes OwlPS usable as is for asset management and emergency positioning of workers underground.
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