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Record W2766278622 · doi:10.1109/icices.2017.8070735

Smart home automation by GSM using android application

2017· article· en· W2766278622 on OpenAlexaff
Shubham Magar, Varsha Saste, Ashwini Lahane, Sangram Konde, Supriya Madne

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIoT-based Smart Home Systems
Canadian institutionsTrinity College
Fundersnot available
KeywordsHome automationAutomationGSMEmbedded systemWirelessComputer scienceProgrammable logic controllerAndroid (operating system)Process automation systemISA100.11aAndroid applicationRemote controlTelecommunicationsEngineeringMultimediaComputer hardwareOperating system

Abstract

fetched live from OpenAlex

The Home automation plays an important role in modern lifestyle because of its access in using at different places with high quality which will intern save time by decreasing human work automatically. The home automation is electric devices stand alone and do not communicate; it is programmable, such as sensors remote controller and communication system. Home automation use for electronic control devices remotely and automatically. This technology is focused on control household appliances like light, fan, AC, etc. automatically. In uncomfortable condition, it is useful for old aged and handicapped person.we have proposed a home appliances control in automation using GSM. The overall design of smart Home Automation system with low cost and wireless system. So the ON/OFF process of home appliances can be done remotely.

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 score0.024
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0240.013

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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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