Evidence map›Paper›PMID 33466895›Full record

ReviewSensors (Basel, Switzerland)2021

Internet of Everything (IoE) Taxonomies: A Survey and a Novel Knowledge-Based Taxonomy.

Viviane Cunha Farias da Costa, Luiz Oliveira, Jano de Souza

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Internet of Things: Security and Solutions Survey.Sensors (Basel, Switzerland) · 2022
    Review
  5. Article
  6. Enabling Blockchain Services for IoE with Zk-Rollups.Sensors (Basel, Switzerland) · 2022
    Review
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Viviane Cunha Farias da CostaSystems Engineering and Computer Science Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-590, Brazil.ORCID 0000-0002-6492-0653
Luiz OliveiraSystems Engineering and Computer Science Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-590, Brazil.ORCID 0000-0002-5890-0701
Jano de SouzaSystems Engineering and Computer Science Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-590, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The paradigm of the Internet of everything (IoE) is advancing toward enriching people's lives by adding value to the Internet of things (IoT), with connections among people, processes, data, and things. This paper provides a survey of the literature on IoE research, highlighting concerns in terms of intelligence services and knowledge creation. The significant contributions of this study are as follows: (1) a systematic literature review of IoE taxonomies (including IoT); (2) development of a taxonomy to guide the identification of critical knowledge in IoE applications, an in-depth classification of IoE enablers (sensors and actuators); (3) validation of the defined taxonomy with 50 IoE applications; and (4) identification of issues and challenges in existing IoE applications (using the defined taxonomy) with regard to insights about knowledge processes. To the best of our knowledge, and taking into consideration the 76 other taxonomies compared, this present work represents the most comprehensive taxonomy that provides the orchestration of intelligence in network connections concerning knowledge processes, type of IoE enablers, observation characteristics, and technological capabilities in IoE applications.

Indexed as

big-dataInternet of everythingInternet of thingsIoEIoTknowledgesensorstaxonomy

Identifiers

PMID33466895
PMCPMC7829822

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.