Sensing Spatial Coverage analysis - for fire detection purposes
Bibliographic record
Abstract
Sensing Spatial Coverage (SSC) is one of the main Quality of Service (QoS) measures in a Wireless Sensor Network (WSN). This quantifies the WSN monitoring ability. The initial phase of WSN implementation is to determine how many sensors with specific sensing ability are required for the intended application or scenario. For this purpose, the sensing profile of the sensors should be known. Most of the previous works considered a Boolean model for the sensors, limiting the sensing ability to a fixed radius known as the sensing range. The sensing ability of the sensors depends on the nature of the application they are used for. In this work fire detection is assumed to be the application and the sensor consists of a simple Infra-red (IR) photodiode. A realistic sensing model will be introduced and the detection ability of the sensor will be studied in detail and closed form formulas will be derived for the probability of fire detection in different distances.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".