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Record W2914876088 · doi:10.22215/etd/2017-11903

An Analysis of an Autonomous Smart House as an Organism: An Alternative Pattern of Organization

2017· dissertation· en· W2914876088 on OpenAlexaff
Nicholas Jewkowicz

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsCarleton University
Fundersnot available
KeywordsOrganismWireless sensor networkSmart gridComputer scienceAdaptation (eye)Living systemsHome automationComplex adaptive systemBiological organismArchitectural engineeringDistributed computingEngineeringArtificial intelligenceTelecommunicationsBiochemical engineeringElectrical engineeringComputer network

Abstract

fetched live from OpenAlex

This paper examines the current state of smart homes and proposes an alternative model based on biomimicry.It is argued that a house that is modeled on a basic living organism will be more efficient for the inhabitants, and more effective to insulate them from the unpredictable effects of climate change in the near future.By using an organism as a model, the house will be able to self-organize its systems, and adapt to both its inhabitants as well as environmental perturbations.This can be accomplished with the use of sensors and actuators in a decentralized configuration with artificial life programming.Since organisms are autonomous by definition, off-grid housing systems are infused to create a new housing model that is zero-emission, zerowaste, and can serve as a model for other forms of infrastructure at greater scales.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.267
Teacher spread0.256 · 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 designSimulation or modeling
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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