Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector

Detalhes bibliográficos
Autor(a) principal: Teixeira, Fabio dos Santos
Data de Publicação: 2020
Outros Autores: Teixeira, Paulo dos Santos, Rocha, Carlos Alberto Machado da
Tipo de documento: Artigo
Idioma: por
Título da fonte: Cadernos de Prospecção (Online)
Texto Completo: https://periodicos.ufba.br/index.php/nit/article/view/32975
Resumo: Artificial intelligence is a technology that allows machines to learn from experiences, adjusting to each new piece of information, performing tasks like humans, enabling construction companies to potentially improve their activities. However, the sector is one of the least digital in the world, implementing innovations at a slower pace. Thus, this article aimed to carry out a prospective study of artificial intelligence solutions with potential for use in the sector, for which the patents filed with INPI and Lens were raised, as well as the scientific productions registered on the CAPES and Science Direct platforms. The prospect pointed to a lack of research and development of products related to the theme. However, the United States stands out in the diffusion of these technologies. Brazil, on the other hand, presented an incipient scenario in its development, although there are already government initiatives to remedy them.
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spelling Prospective Study on Artificial Intelligence Applied to the Civil Construction SectorEstudo Prospectivo Sobre Inteligência Artificial Aplicado ao Setor da Construção CivilProspecçãoInteligência ArtificialConstrução Civil.ProspectingArtificial IntelligenceBuilding Construction.Artificial intelligence is a technology that allows machines to learn from experiences, adjusting to each new piece of information, performing tasks like humans, enabling construction companies to potentially improve their activities. However, the sector is one of the least digital in the world, implementing innovations at a slower pace. Thus, this article aimed to carry out a prospective study of artificial intelligence solutions with potential for use in the sector, for which the patents filed with INPI and Lens were raised, as well as the scientific productions registered on the CAPES and Science Direct platforms. The prospect pointed to a lack of research and development of products related to the theme. However, the United States stands out in the diffusion of these technologies. Brazil, on the other hand, presented an incipient scenario in its development, although there are already government initiatives to remedy them.A inteligência artificial é uma tecnologia que permite que máquinas aprendam com experiências, ajustando-se a cada nova informação, realizando tarefas como humanos, possibilitando às empresas de construção civil um suporte potencial para melhorar suas atividades. Contudo, o setor é um dos menos digitais do mundo, implementando inovações em ritmo mais lento. Dessa forma, o presente artigo teve como objetivo realizar um estudo prospectivo de soluções de inteligência artificial com potencial de utilização no setor, sendo para isso levantadas as patentes depositadas no INPI e no Lens, assim como as produções científicas registradas nas plataformas CAPES e Science Direct. A prospecção apontou uma carência em pesquisa e desenvolvimento de produtos relacionados ao tema. Contudo, os Estados Unidos destacam-se na difusão dessas tecnologias. Já o Brasil, apresentou um cenário incipiente em seu desenvolvimento, embora já existam iniciativas do poder público para saná-las.Universidade Federal da Bahia2020-07-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionProspecção; Revisão de Literaturaapplication/pdfhttps://periodicos.ufba.br/index.php/nit/article/view/3297510.9771/cp.v13i4.32975Cadernos de Prospecção; Vol. 13 No. 4 (2020); 1134Cadernos de Prospecção; v. 13 n. 4 (2020); 11342317-00261983-1358reponame:Cadernos de Prospecção (Online)instname:Universidade Federal da Bahia (UFBA)instacron:UFBAporhttps://periodicos.ufba.br/index.php/nit/article/view/32975/21562Copyright (c) 2020 Cadernos de Prospecçãohttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessTeixeira, Fabio dos SantosTeixeira, Paulo dos SantosRocha, Carlos Alberto Machado da2020-07-12T18:33:55Zoai:ojs.periodicos.ufba.br:article/32975Revistahttps://periodicos.ufba.br/index.php/nitPUBhttps://periodicos.ufba.br/index.php/nit/oaicadernosdeprospeccao@gmail.com || maliceribeiro@yahoo.com.br || cadernosdeprospeccao@gmail.com || saionaraluna@gmail.com2317-00261983-1358opendoar:2020-07-12T18:33:55Cadernos de Prospecção (Online) - Universidade Federal da Bahia (UFBA)false
dc.title.none.fl_str_mv Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
Estudo Prospectivo Sobre Inteligência Artificial Aplicado ao Setor da Construção Civil
title Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
spellingShingle Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
Teixeira, Fabio dos Santos
Prospecção
Inteligência Artificial
Construção Civil.
Prospecting
Artificial Intelligence
Building Construction.
title_short Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
title_full Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
title_fullStr Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
title_full_unstemmed Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
title_sort Prospective Study on Artificial Intelligence Applied to the Civil Construction Sector
author Teixeira, Fabio dos Santos
author_facet Teixeira, Fabio dos Santos
Teixeira, Paulo dos Santos
Rocha, Carlos Alberto Machado da
author_role author
author2 Teixeira, Paulo dos Santos
Rocha, Carlos Alberto Machado da
author2_role author
author
dc.contributor.author.fl_str_mv Teixeira, Fabio dos Santos
Teixeira, Paulo dos Santos
Rocha, Carlos Alberto Machado da
dc.subject.por.fl_str_mv Prospecção
Inteligência Artificial
Construção Civil.
Prospecting
Artificial Intelligence
Building Construction.
topic Prospecção
Inteligência Artificial
Construção Civil.
Prospecting
Artificial Intelligence
Building Construction.
description Artificial intelligence is a technology that allows machines to learn from experiences, adjusting to each new piece of information, performing tasks like humans, enabling construction companies to potentially improve their activities. However, the sector is one of the least digital in the world, implementing innovations at a slower pace. Thus, this article aimed to carry out a prospective study of artificial intelligence solutions with potential for use in the sector, for which the patents filed with INPI and Lens were raised, as well as the scientific productions registered on the CAPES and Science Direct platforms. The prospect pointed to a lack of research and development of products related to the theme. However, the United States stands out in the diffusion of these technologies. Brazil, on the other hand, presented an incipient scenario in its development, although there are already government initiatives to remedy them.
publishDate 2020
dc.date.none.fl_str_mv 2020-07-12
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Prospecção; Revisão de Literatura
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufba.br/index.php/nit/article/view/32975
10.9771/cp.v13i4.32975
url https://periodicos.ufba.br/index.php/nit/article/view/32975
identifier_str_mv 10.9771/cp.v13i4.32975
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufba.br/index.php/nit/article/view/32975/21562
dc.rights.driver.fl_str_mv Copyright (c) 2020 Cadernos de Prospecção
https://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Cadernos de Prospecção
https://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal da Bahia
publisher.none.fl_str_mv Universidade Federal da Bahia
dc.source.none.fl_str_mv Cadernos de Prospecção; Vol. 13 No. 4 (2020); 1134
Cadernos de Prospecção; v. 13 n. 4 (2020); 1134
2317-0026
1983-1358
reponame:Cadernos de Prospecção (Online)
instname:Universidade Federal da Bahia (UFBA)
instacron:UFBA
instname_str Universidade Federal da Bahia (UFBA)
instacron_str UFBA
institution UFBA
reponame_str Cadernos de Prospecção (Online)
collection Cadernos de Prospecção (Online)
repository.name.fl_str_mv Cadernos de Prospecção (Online) - Universidade Federal da Bahia (UFBA)
repository.mail.fl_str_mv cadernosdeprospeccao@gmail.com || maliceribeiro@yahoo.com.br || cadernosdeprospeccao@gmail.com || saionaraluna@gmail.com
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