Win-Shield Combined Biometric and Chemical Sensor System
Bibliographic record
Abstract
The Win-Shield combined biometric and chemical sensor system is a capstone and proof-of-concept project done by the Biosystems Engineering Students of the University of Manitoba over the course of 8 months. The project aims to enhance the safety of isolated industrial workers by providing simultaneous real-time monitoring of vital signs and exposure to hazardous chemicals to both the wearers and their supervisors. Currently, there are no commercially available products designed with these all of these functions for industrial purposes, as most are only intended for recreational or hospital purposes. The system comprises of three subsystems, including a comfort pad with biometric sensors, a chemical sensor unit, and an ESP32ESP32 Devkit microcontroller to process data from the sensors. It can integrate seamlessly into a universal headband to be worn under a welding mask. Key features include: • Having a light weight of 500 grams or under. • Broad applicability fitting 85% of the Canadian population. • Precise vital signs monitoring with temperature accuracy within 0.3°C and 2%. • Heart rate and blood oxygenation accuracy exceeding 97% and 98.85% respectively (Sari et al. 2021). • Alarming chemical exposure thresholds align with 15-minute short term exposure guidelines set by the Government of Manitoba. The design has been verified by various tests resembling CSA standard verification procedures as much as possible under the constraints of time, budget, and resources. For the temperature sensor, immersion in an ice water bath alongside a high-accuracy thermometer assessed accuracy and response time. The heart rate and blood oxygenation sensor has been benchmarked against a smartwatch due to its biometric accuracy. Humidity sensor testing involved controlled environments using salt mixtures to establish fixed relative humidity. Gas sensors have undergone calibration, followed by simple bump testing and limited time response tests, in which they were exposed to triggering gas concentrations within known environments to evaluate response times. The testing section of the report extends its focus to physical tests for the overall system. Environmental temperature, drop, and vibration tests were conducted to ascertain potential impacts on system operation. These tests collectively ensure a robust assessment of the sensor system's reliability and functionality in diverse conditions. Lastly, the limitations that were found to have impacted the design process have been summarized, along with suggestions for potential solutions to these limitations. Additionally, potential next steps for developing this project have been included should the project continue into further design iterations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
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".