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A Remote Intelligent Control System for Split Air Conditioning System

2013· article· en· W2082239523 on OpenAlexaff
Jie Ding, Zhen Zhong Li, Wei Bo Li, Pin He, Yang He

Bibliographic record

VenueApplied Mechanics and Materials · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Control Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChipsetAir conditioningControl systemWirelessIntelligent controlEngineeringControl unitSignal conditioningRemote controlSIGNAL (programming language)Real-time computingEmbedded systemWireless sensor networkComputer scienceControl engineeringChipElectrical engineeringPower (physics)Computer networkTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

Combined wireless sensor network technology (WSN) and infrared control technology this paper designs an intelligent control system for split air conditioner (ACSS). The system adopts the SimpliciTI protocol and a highly integrated chipset, CC1110, as wireless sensing node, which it has high efficiency and lower power. The intelligent remote control unit of the system is capable of signal conversion, wireless communication as well as infrared control ability. In order to suit different air conditioners, the system establishes a control code library by learning a variety of air-conditioning infrared control signals. The control parameters optimized by the system server are transmitted to the intelligent terminal and then fires the infrared control signal to the air conditioner. Therefore, the system achieves the purpose of the remote intelligent controlling.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.183
Teacher spread0.177 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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