Leveraging LoRaWAN to Support IoBT in Urban Environments
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
Continued advances in IoT technology have prompted new investigation into usage of Commercial-off-the-Shelf (COTS) technologies for military operations. Key to these efforts have been expanded empirical research on the coverage of IoT communication protocols in the presence of dense urban infrastructure. Through use of a supporting COTS IoT architecture, a LoRaWAN data collect was conducted in the city of Montreal aimed at testing device coverage over roadways in the downtown area. For this data collect, LoRa performance was compared for different data rate values on the North American Industrial, Scientific, and Medical (ISM) 915 MHz band. This work is seen as a key initial step in supporting expanded usage of civilian IoT communication protocols within tactical C2 systems for urban deployment.
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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) | 0.002 | 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 it