Extração, Integração e Importação de Dados Heterogêneos em Cidades Inteligentes: Um Mapeamento Sistemático

  • João Gabriel Quaresma Almeida Universidade Federal do Rio Grande do Norte
  • Jorge Pereira Silva Universidade Federal do Rio Grande do Norte
  • Everton Ranielly de Sousa Cavalcante Universidade Federal do Rio Grande do Norte
  • Thais Vasconcelos Batista Universidade Federal do Rio Grande do Norte

Resumo


Dados exercem um papel fundamental em cidades inteligentes, sendo utilizados por usuários e aplicações para os mais diferentes propósitos. Como consequência da diversidade de dispositivos e sistemas existentes e da falta de padronização em termos de modelos, protocolos e formatos de dados adotados, observa-se que os dados de cidades inteligentes sãso bastante heterogêneos. Tal heterogeneidade impõe dificuldades ao desenvolvimento de aplicações e utilização desses dados, fazendo com que seja necessário investigar estratégias e soluções para extração, integração e importação de dados em ambientes de cidades inteligentes. A fim de prover um panorama do atual estado da arte com relação a esse tópico, foi realizado um mapeamento sistemático no qual 28 estudos disponíveis na literatura foram coletados e analisados para identificar estratégias, metodologias e facilidades existentes para apoiar e implementar essas atividades. Este artigo apresenta os principais resultados do mapeamento sistemático realizado, bem como um conjunto de desafios de pesquisa e desenvolvimento que podem direcionar trabalhos futuros.

Palavras-chave: Cidades inteligentes, Dados heterogêneos, Extração de dados, Integração de dados, Importação de dados, Mapeamento sistemático

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Publicado
10/12/2020
ALMEIDA, João Gabriel Quaresma; SILVA, Jorge Pereira; CAVALCANTE, Everton Ranielly de Sousa; BATISTA, Thais Vasconcelos. Extração, Integração e Importação de Dados Heterogêneos em Cidades Inteligentes: Um Mapeamento Sistemático. In: WORKSHOP DE COMPUTAÇÃO URBANA (COURB), 4. , 2020, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 57-70. ISSN 2595-2706. DOI: https://doi.org/10.5753/courb.2020.12353.