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Developing an Architecture for IoT Interoperability in Healthcare: A Case Study of Real-time SpO2 Signal Monitoring and Analysis

2020· article· en· W3137195139 on OpenAlexaff
Quoc Hung Nguyen, Quang Dang, Chuan Pham, Tien-Dung Nguyen, Hang Nguyen, Arveity R. Setty, Trung Q. Le

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsÉcole de Technologie Supérieure
FundersNational Institutes of Health
KeywordsInteroperabilityArchitectureInternet of ThingsComputer scienceHealth careSIGNAL (programming language)Embedded systemReal-time computingReal-time locating systemWorld Wide WebGeography

Abstract

fetched live from OpenAlex

The article presents a novel approach to address the interoperability issues in the Internet of Things (IoT) systems. Based on the IoT Reference Architecture, an IoT system architecture integrated with gateways and data converter solutions has been proposed to enhance the information exchange and data sharing across interconnected devices, networks and platforms. In addition, distributed open-source analytic platforms for real-time computational and streaming processing has been introduced to the proposed architecture. A case study of real-time oxygen saturation (SpO2) monitoring and analysis has been implemented to demonstrate the feasibility of the proposed architecture. The experimental results show the efficiency in terms of collecting and analyzing large volumes of data.

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)0.004
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.325
Teacher spread0.265 · 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
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

Citations8
Published2020
Admission routes1
Has abstractyes

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