Internet of Everything (IoE) Taxonomy
Authors:
Autores
Person role | Person | |
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6904 |
2087,3021,10
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6905 |
2087,3021,10
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6906 |
2087,3021,10
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Informations:
Pesc publication
O paradigma Internet de Tudo ou “Internet of Everything” (IoE) é um superconjunto da Internet of Things (IoT) e reúne, conceitualmente e virtualmente, pessoas, processos, dados e coisas em conexões de rede inteligentes e processos de conhecimento. Esses "serviços inteligentes" compõem o "tudo" na IoE [7].
Os aplicativos da IoE exigem que medidas adequadas sejam tomadas nas fases iniciais de seu desenvolvimento. Portanto, existem oportunidades de pesquisa em relação aos insights sobre as características dos sensores/atuadores de IoE (pessoas e coisas): (1) como eles são combinados e usados em diferentes domínios de aplicação. Além disso, (2) como as questões relacionadas às suas capacidades e observações podem afetar a qualidade dos serviços inteligentes e a criação de conhecimento.
Para esclarecer esse assunto, abordamos a seguinte questão de pesquisa: Como os sensores/atuadores de IoE podem ser classificados com base no conhecimento que fornecem em tarefas inteligentes?
E para responder a esta questão de pesquisa, conduzimos uma revisão sistemática da literatura das taxonomias IoE e IoT existentes. A partir disso, pudemos apresentar uma taxonomia IoE baseada no conhecimento, de acordo com o método de desenvolvimento de taxonomia de Nickerson et al. [8]. A taxonomia de IoE proposta fornece uma imagem consistente de sistemas de IoE e seus constituintes (ou seja, sensores e atuadores de IoE caracterizados em processos de conhecimento, observações e características de rede). Em seguida, validamos a taxonomia definida com 50 aplicativos de IoE para provar seus atributos de qualidade e identificar desafios de pesquisa. Uma análise mais detalhada da revisão sistemática da literatura foi submetida ao Sensors Journal.
The paradigm of the Internet of Everything (IoE) is a superset of the Internet of Things (IoT) [1] with connections among people, processes, data, and things. While IoT is concerned about things, IoE lays an upper foundation over IoT concept by connecting devices and people in one network [2], concerning intelligent network connections [3]–[6] and knowledge processes. These "intelligent services" compose the "everything" in IoE [7]. Figure 1 shows the "four pillars" of people, data, processes, and things in IoE.
IoE applications demand appropriate measures to be taken in the initial phases of its design and implementation [1]. Thus, there is a research gap regarding insights into IoE enablers' characteristics (people and things): (1) how they are combined and used as sensors and actuators in different application domains. Moreover, (2) how issues related to their capabilities and observations can affect the quality of intelligent services and knowledge creation.
To clarify this matter, we addressed the following research question: How can IoE enablers be classified based on the knowledge they provide in intelligent tasks?
And to answer this research issue, we conducted a systematic literature review of existing IoE and IoT taxonomies. From this, we were able to present a knowledge-based IoE taxonomy, according to the taxonomy development method by Nickerson et al. [8]. The proposed IoE taxonomy provides a consistent picture of IoE systems and their constituents (i.e., IoE sensors and actuators characterized in knowledge processes, observations, and network characteristics). We then validated the defined taxonomy with 50 IoE applications to prove its quality attributes and identify research challenges. A more detailed analysis of the systematic literature review has been submitted to the Sensors Journal.
The proposed IoE taxonomy consists of four categories (Knowledge, Type, Observation, Capabilities), which groups 18 dimensions composed of mutually exclusive and collectively exhaustive characteristics:
(1) The Knowledge category relates to knowledge and information flow and contains five dimensions: Explicitness, Structure, Trust, Outcome, and Action.
(2) The Type category classifies sensors and actuators and contains five subcategories: Presentation, Nature, Use, Role, and Engagement.
(3) The Observation category relates to sensed context and contains five subcategories: Location, Reach, Mobility, Time, and Mode.
(4) The Capabilities category refers to the processing power and storage capacity of sensors and contains three subcategories: Communication, Processing, and Storage.