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Record W4225274282 · doi:10.1016/j.dcan.2022.04.027

Internet of things: Conceptual network structure, main challenges and future directions

2022· article· en· W4225274282 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

VenueDigital Communications and Networks · 2022
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsYork UniversityLakehead University
FundersMinisterio de Ciencia e InnovaciónConsejo Nacional de Ciencia y TecnologíaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsComputer scienceKey (lock)Internet of ThingsData scienceThematic analysisThe InternetConceptual frameworkThematic mapWorld Wide WebCluster (spacecraft)Knowledge managementComputer securityQualitative research

Abstract

fetched live from OpenAlex

Internet of Things (IoT) is a key technology trend that supports our digitalized society in applications such as smart countries and smart cities. In this study, we investigated the existing strategic themes, thematic evolution structure, key challenges, and potential research opportunities associated with the IoT. For this study, we conducted a Bibliometric Performance and Network Analysis (BPNA), supplemented by an exhaustive Systematic Literature Review (SLR). Specifically, in BPNA, the software SciMAT was used to analyze 14,385 documents and 30,381 keywords in the Web of Science (WoS) database, which was released between 2002 and 2019. The results revealed that 31 clusters are classified according to their importance and development, and the conceptual structures of key clusters are presented, along with their performance analysis and the relationship with other subthemes. The thematic evolution structure described the important cluster(s) over time. For the SLR, 23 documents were analyzed. The SLR revealed key challenges and limitations associated with the IoT. We expect the results will form the basis of future research and guide decision-making in the IoT and other supporting industries.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.420

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 science0.0010.002
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 head0.025
GPT teacher head0.227
Teacher spread0.202 · 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