LoRa Wireless Link Performance in Multipath Underground Mines
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
It has become a challenge to effectively maintain higher levels of safety and productivity in mining operations due to the present-day smart IoT technology advancements in mining equipment and gadgets. Regardless of the complexity of IoT schemes, all the systems rely on one common factor - an effective and reliable transportation mechanism for data and control information from/to the smart devices. Therefore, the communication infrastructure in confined spaces is the most critical element in the smart system operation. This is especially true due to the limitations and complications of physical phenomena affecting the wireless system and networks in the mines and tunnels. Strong multipath nature of the wireless channel affects the smart wireless communication significantly in underground mine. In this paper, we use LoRa technology to provide better connectivity in harsh environment such as in mines. With its long range, deep penetration, and ultralow power consumption and single hop wireless communication technology; LoRa provides reliable connectivity to previously infeasible underground mining environment. This paper presents simulation study that provide LoRa performance in mining area with strong multipath conditions for different spread factors (SF).
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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) | 0.000 | 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