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A Remote Intelligent Control System for Split Air Conditioning System

2013· article· en· W2082239523 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

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.776

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)0.0000.000

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 head0.006
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