Data science for Industry 4.0 and sustainability: a survey and analysis based on open data
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/85538 |
Resumo: | In the last few years, the industrial, scientific, and technological fields have been subject to a revolutionary process of digitalization and automation called Industry 4.0. Its implementation has been successful mainly in the economic field of sustainability, while the environmental field has been gaining more attention from researchers recently. However, the social scope of Industry 4.0 is still somewhat neglected by researchers and organizations. This research aimed to study Industry 4.0 and sustainability themes using data science, by incorporating open data and open-source tools to achieve sustainable Industry 4.0. To that end, a quantitative analysis based on open data was developed using open-source software in order to study Industry 4.0 and sustainability trends. The main results show that manufacturing is a relevant value-added activity in the worldwide economy; that, foreseeing the importance of Industry 4.0, countries in America, Asia, Europe, and Oceania are incorporating technological principles of Industry 4.0 in their cities, creating so-called smart cities; and that the industries that invest most in technology are computers and electronics, pharmaceuticals, transport equipment, and IT (information technology) services. Furthermore, the G7 countries have a prevalent positive trend for the migration of technological and social skills toward sustainability, as it relates to the social pillar, and to Industry 4.0. Finally, on the global scale, a positive correlation between data openness and happiness was found. |
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Data science for Industry 4.0 and sustainability: a survey and analysis based on open dataIndustry 4.0Data scienceSustainabilitySocial sustainability open dataOpen-source toolsIndustry 40Science & TechnologyIn the last few years, the industrial, scientific, and technological fields have been subject to a revolutionary process of digitalization and automation called Industry 4.0. Its implementation has been successful mainly in the economic field of sustainability, while the environmental field has been gaining more attention from researchers recently. However, the social scope of Industry 4.0 is still somewhat neglected by researchers and organizations. This research aimed to study Industry 4.0 and sustainability themes using data science, by incorporating open data and open-source tools to achieve sustainable Industry 4.0. To that end, a quantitative analysis based on open data was developed using open-source software in order to study Industry 4.0 and sustainability trends. The main results show that manufacturing is a relevant value-added activity in the worldwide economy; that, foreseeing the importance of Industry 4.0, countries in America, Asia, Europe, and Oceania are incorporating technological principles of Industry 4.0 in their cities, creating so-called smart cities; and that the industries that invest most in technology are computers and electronics, pharmaceuticals, transport equipment, and IT (information technology) services. Furthermore, the G7 countries have a prevalent positive trend for the migration of technological and social skills toward sustainability, as it relates to the social pillar, and to Industry 4.0. Finally, on the global scale, a positive correlation between data openness and happiness was found.This work was financed by national funds through the Portuguese funding agency, FCT—Fundação para a Ciência e a Tecnologia, within project LA/P/0063/2020.Multidisciplinary Digital Publishing InstituteUniversidade do MinhoCastro, HélioCosta, FilipeFerreira, TâniaÁvila, PauloCruz-Cunha, ManuelaFerreira, LuísPutnik, Goran D.Bastos, João2023-04-032023-04-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/85538engCastro, H.; Costa, F.; Ferreira, T.; Ávila, P.; Cruz-Cunha, M.; Ferreira, L.; Putnik, G.D.; Bastos, J. Data Science for Industry 4.0 and Sustainability: A Survey and Analysis Based on Open Data. Machines 2023, 11, 452. https://doi.org/10.3390/machines110404522075-170210.3390/machines11040452https://www.mdpi.com/2075-1702/11/4/452info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:09:17Zoai:repositorium.sdum.uminho.pt:1822/85538Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:00:40.635885Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data |
title |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data |
spellingShingle |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data Castro, Hélio Industry 4.0 Data science Sustainability Social sustainability open data Open-source tools Industry 4 0 Science & Technology |
title_short |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data |
title_full |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data |
title_fullStr |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data |
title_full_unstemmed |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data |
title_sort |
Data science for Industry 4.0 and sustainability: a survey and analysis based on open data |
author |
Castro, Hélio |
author_facet |
Castro, Hélio Costa, Filipe Ferreira, Tânia Ávila, Paulo Cruz-Cunha, Manuela Ferreira, Luís Putnik, Goran D. Bastos, João |
author_role |
author |
author2 |
Costa, Filipe Ferreira, Tânia Ávila, Paulo Cruz-Cunha, Manuela Ferreira, Luís Putnik, Goran D. Bastos, João |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Castro, Hélio Costa, Filipe Ferreira, Tânia Ávila, Paulo Cruz-Cunha, Manuela Ferreira, Luís Putnik, Goran D. Bastos, João |
dc.subject.por.fl_str_mv |
Industry 4.0 Data science Sustainability Social sustainability open data Open-source tools Industry 4 0 Science & Technology |
topic |
Industry 4.0 Data science Sustainability Social sustainability open data Open-source tools Industry 4 0 Science & Technology |
description |
In the last few years, the industrial, scientific, and technological fields have been subject to a revolutionary process of digitalization and automation called Industry 4.0. Its implementation has been successful mainly in the economic field of sustainability, while the environmental field has been gaining more attention from researchers recently. However, the social scope of Industry 4.0 is still somewhat neglected by researchers and organizations. This research aimed to study Industry 4.0 and sustainability themes using data science, by incorporating open data and open-source tools to achieve sustainable Industry 4.0. To that end, a quantitative analysis based on open data was developed using open-source software in order to study Industry 4.0 and sustainability trends. The main results show that manufacturing is a relevant value-added activity in the worldwide economy; that, foreseeing the importance of Industry 4.0, countries in America, Asia, Europe, and Oceania are incorporating technological principles of Industry 4.0 in their cities, creating so-called smart cities; and that the industries that invest most in technology are computers and electronics, pharmaceuticals, transport equipment, and IT (information technology) services. Furthermore, the G7 countries have a prevalent positive trend for the migration of technological and social skills toward sustainability, as it relates to the social pillar, and to Industry 4.0. Finally, on the global scale, a positive correlation between data openness and happiness was found. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-04-03 2023-04-03T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/85538 |
url |
https://hdl.handle.net/1822/85538 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Castro, H.; Costa, F.; Ferreira, T.; Ávila, P.; Cruz-Cunha, M.; Ferreira, L.; Putnik, G.D.; Bastos, J. Data Science for Industry 4.0 and Sustainability: A Survey and Analysis Based on Open Data. Machines 2023, 11, 452. https://doi.org/10.3390/machines11040452 2075-1702 10.3390/machines11040452 https://www.mdpi.com/2075-1702/11/4/452 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute |
publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799132403026886656 |