Descoberta Dinâmica de Serviços em IoT Baseado em Fluxos de Informações Semânticas de Smart Objects.

• Ano de defesa: 2019
• Autor(a) principal: COSTA, Anderson Soares
• Orientador(a): SILVA, Francisco José da Silva e
• Banca de defesa: SILVA, Francisco José da Silva e , LOPES, Denivaldo Cícero Pavão , RORIZ JUNIOR, Marcos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Maranhão
• Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
• Departamento: DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
• País: Brasil
• Palavras-chave em Português: Descoberta de serviço; Representação Semântica; Internet das Coisas; Ontologia; Bases de Conhecimento
• Palavras-chave em Inglês: Service Discovery; Semantic Representation; Internet of Things; Ontology; Knowledge Bases
• Área do conhecimento CNPq: Linguagem Formais e Automatos.
• Link de acesso: https://tedebc.ufma.br/jspui/handle/tede/2742

The Internet of Things (IoT) is a combination of ubiquitous computing and the Internet, in which IoT (smart objects) devices can collect and exchange data, cooperating with people and the environment in which they find themselves. The Internet of Things Mobile (IoMT), which is an extension of IoT, proposes scenarios in which smart objects and gateways are mobile. In this context, this work is focused on the discovery of smart objects in IoT/IoMT environments considering the following problems: mobility of both smart objects and gateways; great heterogeneity of smart objects and communication technologies to access them; the need for interoperability in these environments; the need to combine data from smart objects with knowledge bases. Therefore, the objective of this work is to combine Semantic Flow Processing with knowledge representation techniques to enrich the instantaneous and continuous discovery of smart objects and their services in IoT/IoMT environments. To this end, an ontology was developed to describe IoT/IoMT scenarios, a semantic middleware, an API for building information systems and applications, and a cloud infrastructure for querying and semantic streaming of smart objects. The qualitative evaluation of this work is done through a use case in the field of intelligent parking, which served to show that the proposed mechanisms apply to several application domains. The quantitative evaluation proved the efficiency of the solution in relation to the processing time of each component, besides the identification of the influence factors in the time of the semantic processing.