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Record W2378769119

Intelligent Sensor Design Based on Wi-Fi

2011· article· en· W2378769119 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMicrocomputer applications · 2011
Typearticle
Languageen
FieldEngineering
TopicWireless Sensor Networks and IoT
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceWireless sensor networkSignal conditioningEmbedded systemInternet of ThingsIntelligent sensorWirelessPower consumptionEnergy consumptionReal-time computingComputer hardwarePower (physics)Electrical engineeringTelecommunicationsComputer network
DOInot available

Abstract

fetched live from OpenAlex

As the development of internet of things,the intelligence and low power consumption of sensor are becoming increasingly important.Based on this,a new type of intelligent sensor based on Wi-Fi is designed,which uses the ultra-low power SoC GS1011 as the controlling center.The hardware part consists of sensors,signal conditioning module,sampling and storage module and processing module,and the ping-pong-type storage structure is used to save energy of the system.The application development of intelligent sensor is based on Green Hills operating system.The experimental results show that the design of intelligent sensor has good performance and stability of wireless communications.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.415
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.029
GPT teacher head0.202
Teacher spread0.173 · 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