Implementation of Monitoring System for Air Quality using Raspberry PI: Experimental Study
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
<span lang="EN-US">Because of rising dependency on fossil fuels, and rising amounts of toxic gases in the environment, it found that people are in need of a way to ensure the safety specifically those that live in cities. An approach is suggested in this paper, that is economical yet affords good detection, and can give accurate readings that can be analyzed and manipulated, and can even provide warnings through sending emails. These requirements are found in the Raspberry Pi when it hooked up to the sensors. This paper was focused on few dangerous gases such as Carbon Monoxide (CO), Nitrogen Dioxide (NO2) and other gases. The results in this paper showed that some gases, specifically CO, may be a problem in Kuwait as it is always slightly below the warning level. The success with the Raspberry Pi and the results were encouraging to open the way for much improvement in the future.</span>
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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