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Record W2529923148 · doi:10.2991/ict4s-16.2016.22

Sustainable and Smart: Rethinking What a Smart Home is

2016· article· en· W2529923148 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
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of TorontoYorkville University
Fundersnot available
KeywordsSustainabilityArchitectural engineeringHome automationEntertainmentResource (disambiguation)Computer scienceResource efficiencySmart environmentArchitectureSmart lightingInformation and Communications TechnologyDependency (UML)Internet of ThingsComputer securityEngineeringTelecommunicationsPolitical scienceWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

The term Smart Home typically refers to dwellings augmented with high-tech responsive systems such that heating, air conditioning, lighting, appliances, entertainment outlets, and architectural components are computerized and managed, often via a remote control. Smart homes promise comfort, convenience, and resource conservation in the near future. Yet the notion of increased dependency on technology for comfort and efficiency (and hence, sustainably) needs to be revised. While we (justifiably) expect our dwellings to use technological advances to sense and respond to our needs, a growing body of literature [1-5] warns against increased dependencies and amplified complexification, given the resource depletion anticipated in the future. Through examples and discussions drawn primarily from vernacular architecture discourse, this paper addresses this dichotomy. We investigate how smart homes can be re-defined to better fit sustainability goals while anticipating technology limitations. We introduce members of the ICT4S community to the sustainability potentials of vernacular domestic architecture and inspire them by its smart responses to human needs and harsh conditions. And finally, we argue that re-employing tried-and-true vernacular techniques in conjunction with ICT systems can offer smart yet simple and feasible solutions to future housing needs while being inherently more sustainable from an environmental and operational stance.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.323

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 communication0.0000.004
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 head0.016
GPT teacher head0.252
Teacher spread0.236 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

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