Reliability of ZigBee networks under broadband electromagnetic noise interference
Bibliographic record
Abstract
The goal of this paper is to determine the robustness of the ZigBee wireless networking technology under the influence of interference caused by broadband electromagnetic noise from the operating environment of sensing, monitoring, and control systems. Broadband electromagnetic noise was of interest because such electrical noise (i) does exist and is prevalent due to emissions from electrical and electronic components nearby the communication system, and (ii) can cause interference across multiple (wireless) channels. Therefore, such noise will need to be characterized and modeled to assess its effects upon the performance of a wireless system as well as for devising noise control methods. In addition to answering the research question of how will ZigBee survive under broadband electromagnetic noise, this work also provides a method to predict the minimum number of ZigBee nodes required for reliable operation within a given space. These two questions have neither been answered in the ZigBee specification nor in any existing research publications.
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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 | 0.000 |
| 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 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".