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Record W2070658900 · doi:10.1109/iot.2014.7030119

IoT interoperability: A hub-based approach

2014· article· en· W2070658900 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
TopicIoT and Edge/Fog Computing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInteroperabilityInternet of ThingsComputer scienceContext (archaeology)Semantic interoperabilityWorld Wide WebCross-domain interoperabilitySoftware engineeringData science

Abstract

fetched live from OpenAlex

Interoperability in the Internet of Things is critical for emerging services and applications. In this paper we advocate the use of IoT `hubs' to aggregate things using web protocols, and suggest a staged approach to interoperability. In the context of a UK government funded project involving 8 IoT sub-projects to address cross-domain IoT interoperability, we introduce the HyperCat IoT catalogue specification. We then describe the tools and techniques we developed to adapt an existing data portal and IoT platform to this specification, and provide an IoT hub focused on the highways industry called `Smart Streets'. Based on our experience developing this large scale IoT hub, we outline lessons learned which we hope will contribute to ongoing efforts to create an interoperable global IoT ecosystem.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.336

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 science0.0010.000
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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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

Citations115
Published2014
Admission routes1
Has abstractyes

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