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Record W1967073889 · doi:10.1109/cnsr.2010.62

Experimental Testing of IEEE801.15.4/ZigBee Sensor Networks in Confined Area

2010· article· en· W1967073889 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsQuest University CanadaUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsWireless sensor networkNeuRFonAutomationComputer scienceIEEE 802.15WirelessHazardous wasteComputer networkActuatorEmbedded systemWireless networkKey distribution in wireless sensor networksEngineeringTelecommunications

Abstract

fetched live from OpenAlex

The IEEE 802.15.4/ZigBee™ standard is considered as a potential candidate for wireless sensor and actuators networks. Several commercial platforms with IEEE 802.15.4/ZigBee support have been made available in the last few years, and an increasing number of operating systems specifically designed for sensor and actuator networks are evolving. Underground mining is considered to be one of most hazardous industrial activity. The industrial automation applications in the mining galleries can benefit from the recent technological advances. In fact, many approaches to reduce costs and improve performance have been examined. The main objective of this paper is the implementation and evaluation of wireless sensor networks for environmental data measurements in a real underground mine. Therefore, the nodes were evaluated in real operating conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.233
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations25
Published2010
Admission routes1
Has abstractyes

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