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Review

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

1
Systems Engineering and Computer Science Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-590, Brazil
2
Federal Institute of Rio de Janeiro, Niterói Campus, Niterói 24315-375, Brazil
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(2), 568; https://doi.org/10.3390/s21020568
Received: 29 November 2020 / Revised: 7 January 2021 / Accepted: 8 January 2021 / Published: 14 January 2021
(This article belongs to the Special Issue Internet of Things, Big Data and Smart Systems)
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. View Full-Text
Keywords: Internet of everything; Internet of things; IoE; IoT; taxonomy; sensors; big-data; knowledge Internet of everything; Internet of things; IoE; IoT; taxonomy; sensors; big-data; knowledge
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MDPI and ACS Style

Farias da Costa, V.C.; Oliveira, L.; de Souza, J. Internet of Everything (IoE) Taxonomies: A Survey and a Novel Knowledge-Based Taxonomy. Sensors 2021, 21, 568. https://doi.org/10.3390/s21020568

AMA Style

Farias da Costa VC, Oliveira L, de Souza J. Internet of Everything (IoE) Taxonomies: A Survey and a Novel Knowledge-Based Taxonomy. Sensors. 2021; 21(2):568. https://doi.org/10.3390/s21020568

Chicago/Turabian Style

Farias da Costa, Viviane Cunha, Luiz Oliveira, and Jano de Souza. 2021. "Internet of Everything (IoE) Taxonomies: A Survey and a Novel Knowledge-Based Taxonomy" Sensors 21, no. 2: 568. https://doi.org/10.3390/s21020568

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