Low-Cost UAV-Based Air Quality and Temperature Monitoring System
Bibliographic record
Abstract
This paper presents an economical UAV system that performs real-time environmental monitoring, including air quality and temperature measurements. The system comprises a Grove multichannel gas sensor and a DHT11 temperature and humidity sensor, which operate under ESP32 microcontroller control, along with a LoRa module for extended-range, low-power data transmission within a 228-gram payload. The system utilizes a local IP-based IoT dashboard to display real-time data, eliminating the need for cellular or cloud connectivity. The system demonstrated its ability to detect spatial and vertical environmental patterns through field tests, which measured gas sensor indices and temperature and humidity profiles in residential, industrial, and academic areas at heights up to 25 meters. The proposed system enables scalable urban air-quality monitoring through commercial UAVs without requiring any infrastructure. The system will receive future improvements through sensor calibration, GPS-based geotagging, and the integration of PM2.5and O3sensing modules to enhance measurement accuracy and system functionality.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".