Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings

Detalhes bibliográficos
Autor(a) principal: Justino, Marcelo Pereira
Data de Publicação: 2020
Outros Autores: Silva, Fernando Selleri, Rabelo, Olivan da Silva
Tipo de documento: Artigo
Idioma: por
Título da fonte: Cadernos de Prospecção (Online)
Texto Completo: https://periodicos.ufba.br/index.php/nit/article/view/33079
Resumo: This paper aimed to survey the use of artificial intelligence (AI) for energy efficiency management in public buildings. It used the qualitative approach, with exploratory objective on the subject in question, relying on bibliographic research, in the basis of scientific and documentary publications, in Brazilian government agencies on energy efficiency, and technological prospection. The keywords used were "artificial intelligence AND energy efficiency AND public buildings", the search in Scopus returned 1,459 articles referring to the object of work. Most affiliate documents belong to Chinese and European educational institutions, although the United States ranks first in number of publications by country. As for technological prospection, most patents also belong to universities, but in this case, especially China. Because artificial intelligence is a broad term, it enables the development of future work in greater depth in a specific branch of AI.
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spelling Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public BuildingsPerspectiva de Uso da Inteligência Artificial (IA) para a Eficiência Energética em Prédios PúblicosAprendizado de MáquinaAutomaçãoEdificações Públicas.Machine LearningAutomationPublic Buildings.This paper aimed to survey the use of artificial intelligence (AI) for energy efficiency management in public buildings. It used the qualitative approach, with exploratory objective on the subject in question, relying on bibliographic research, in the basis of scientific and documentary publications, in Brazilian government agencies on energy efficiency, and technological prospection. The keywords used were "artificial intelligence AND energy efficiency AND public buildings", the search in Scopus returned 1,459 articles referring to the object of work. Most affiliate documents belong to Chinese and European educational institutions, although the United States ranks first in number of publications by country. As for technological prospection, most patents also belong to universities, but in this case, especially China. Because artificial intelligence is a broad term, it enables the development of future work in greater depth in a specific branch of AI.Este trabalho realizou o levantamento do uso de Inteligência Artificial (IA) para a gestão de eficiência energética em prédios públicos. Utilizou-se da abordagem qualitativa, com objetivo exploratório sobre o tema em questão, apoiando-se na pesquisa bibliográfica, em bases de publicações científicas e documental, em órgãos do governo brasileiro sobre eficiência energética e prospecção tecnológica. As palavras-chave utilizadas foram “artificial intelligence AND energy efficiency AND public buildings”, a busca na Scopus retornou 1.459 artigos referentes ao objeto deste trabalho. A maioria dos documentos por afiliações pertence a instituições de ensino chinesas e europeias, embora tenha se notado que Estados Unidos ocupa a primeira posição em número de publicações por país. Quanto à prospecção tecnológica, a maioria das patentes pertence, também, a universidades, mas, neste caso, a China se destaca. Como Inteligência Artificial é um termo abrangente, isso possibilita o desenvolvimento de trabalhos futuros com maior aprofundamento em um ramo específico da IA.Universidade Federal da Bahia2020-05-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufba.br/index.php/nit/article/view/3307910.9771/cp.v13i3.33079Cadernos de Prospecção; Vol. 13 No. 3 (2020); 769Cadernos de Prospecção; v. 13 n. 3 (2020); 7692317-00261983-1358reponame:Cadernos de Prospecção (Online)instname:Universidade Federal da Bahia (UFBA)instacron:UFBAporhttps://periodicos.ufba.br/index.php/nit/article/view/33079/21139Copyright (c) 2020 Cadernos de Prospecçãohttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessJustino, Marcelo PereiraSilva, Fernando SelleriRabelo, Olivan da Silva2020-05-29T17:35:10Zoai:ojs.periodicos.ufba.br:article/33079Revistahttps://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:2020-05-29T17:35:10Cadernos de Prospecção (Online) - Universidade Federal da Bahia (UFBA)false
dc.title.none.fl_str_mv Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
Perspectiva de Uso da Inteligência Artificial (IA) para a Eficiência Energética em Prédios Públicos
title Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
spellingShingle Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
Justino, Marcelo Pereira
Aprendizado de Máquina
Automação
Edificações Públicas.
Machine Learning
Automation
Public Buildings.
title_short Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
title_full Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
title_fullStr Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
title_full_unstemmed Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
title_sort Perspective on the Use of Artificial Intelligence for Energy Efficiency in Public Buildings
author Justino, Marcelo Pereira
author_facet Justino, Marcelo Pereira
Silva, Fernando Selleri
Rabelo, Olivan da Silva
author_role author
author2 Silva, Fernando Selleri
Rabelo, Olivan da Silva
author2_role author
author
dc.contributor.author.fl_str_mv Justino, Marcelo Pereira
Silva, Fernando Selleri
Rabelo, Olivan da Silva
dc.subject.por.fl_str_mv Aprendizado de Máquina
Automação
Edificações Públicas.
Machine Learning
Automation
Public Buildings.
topic Aprendizado de Máquina
Automação
Edificações Públicas.
Machine Learning
Automation
Public Buildings.
description This paper aimed to survey the use of artificial intelligence (AI) for energy efficiency management in public buildings. It used the qualitative approach, with exploratory objective on the subject in question, relying on bibliographic research, in the basis of scientific and documentary publications, in Brazilian government agencies on energy efficiency, and technological prospection. The keywords used were "artificial intelligence AND energy efficiency AND public buildings", the search in Scopus returned 1,459 articles referring to the object of work. Most affiliate documents belong to Chinese and European educational institutions, although the United States ranks first in number of publications by country. As for technological prospection, most patents also belong to universities, but in this case, especially China. Because artificial intelligence is a broad term, it enables the development of future work in greater depth in a specific branch of AI.
publishDate 2020
dc.date.none.fl_str_mv 2020-05-29
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufba.br/index.php/nit/article/view/33079
10.9771/cp.v13i3.33079
url https://periodicos.ufba.br/index.php/nit/article/view/33079
identifier_str_mv 10.9771/cp.v13i3.33079
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufba.br/index.php/nit/article/view/33079/21139
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. 3 (2020); 769
Cadernos de Prospecção; v. 13 n. 3 (2020); 769
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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