Underwater temperature and pressure monitoring for deep-sea SCUBA divers using optical techniques
Bibliographic record
Abstract
The safety of SCUBA divers remains at high risk in deep-sea owing to multiple factors such as dangerous surrounding, rely upon technical equipment necessary for life support, decreased underwater navigation, and communication infrastructure. Gradual decrease and increase in water temperature and pressure corresponding to depth are among the most common problems that cause most of the fatalities in deep-sea diving. Therefore, different gadgets for accurate measurement of vital parameters, reliable navigation, and seamless communication are of prime importance. In this paper, we propose an all-optical technique for local and remote monitoring of underwater temperature and pressure for deep-sea SCUBA divers based on fiber Bragg grating (FBG) sensors and underwater optical communication-single mode fiber (UWOC-SMF) integrated transmission system. The proposed technique is implemented using two FBG temperature and pressure sensors fixed over diver’s suit and UWOC-SMF integrated transmission system for simultaneous local and remote monitoring of underwater temperature and pressure. Remote monitoring of underwater temperature and pressure is achieved at ship station through a remotely operated underwater vehicle (ROV) and UWOC-SMF integrated transmission system by means of shifts in the original Bragg wavelengths of sensors due to temperature and pressure variations. The performance of the sensors is analyzed for pressure and temperature in the range of 0 to 6.4 MPa ( ≈ 0 to 655 m H 2 O ) and 40 to −2 °C , respectively corresponding to different depths. The results show that the proposed technique can work well in the deep ocean over a range of pressures and temperatures of 0–7 MPa and 40 to −2 °C while achieving a temperature sensitivity of 4.3 p.m./ ° C and a pressure sensitivity of 30.5 p.m./MPa. Clear spectra of reflected signals from FBG sensors at ship station are achieved after signal transmission over UWOC-SMF hybrid link.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".