Deepint.net: A rapid deployment platform for smart territories
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/71925 |
Resumo: | This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques. |
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Deepint.net: A rapid deployment platform for smart territoriessmart citiessmart cyberphysical platformdata analysisdata visualizationedge computingartificial intelligencebike rentingCiências Naturais::Ciências da Computação e da InformaçãoScience & TechnologyThis paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques.This work has been partially supported by the European Regional Development Fund (ERDF) through the Interreg Spain-Portugal V-A Program (POCTEP) under grant 0677_DISRUPTIVE_2_E, the project My-TRAC: My TRAvel Companion (H2020-S2RJU-2017), the project LAPASSION, CITIES (CYTED 518RT0558) and the company DCSC. Pablo Chamoso’s research work has been funded through the Santander Iberoamerican Research Grants, call 2020/2021, under the direction of Paulo Novais.Multidisciplinary Digital Publishing InstituteUniversidade do MinhoCorchado, Juan M.Chamoso, PabloHernández, GuillermoGutierrez, Agustín San RomanCamacho, Alberto RivasGonzález-Briones, AlfonsoPinto-Santos, FranciscoGoyenechea, EnriqueGarcia-Retuerta, DavidAlonso-Miguel, MaríaHernandez, Beatriz BellidoVillaverde, Diego ValdeolmillosSanchez-Verdejo, ManuelPlaza-Martínez, PabloLópez-Pérez, ManuelManzano-García, SergioAlonso, Ricardo S.Casado-Vara, RobertoTejedor, Javier PrietoPrieta, Fernando de laRodríguez-González, SaraParra-Domínguez, JavierMohamad, Mohd SaberiTrabelsi, SaberDíaz-Plaza, EnriqueGarcia-Coria, Jose AlbertoYigitcanlar, TanNovais, PauloOmatu, Sigeru20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/71925engCorchado, J.M.; Chamoso, P.; Hernández, G.; Gutierrez, A.S.R.; Camacho, A.R.; González-Briones, A.; Pinto-Santos, F.; Goyenechea, E.; Garcia-Retuerta, D.; Alonso-Miguel, M.; Hernandez, B.B.; Villaverde, D.V.; Sanchez-Verdejo, M.; Plaza-Martínez, P.; López-Pérez, M.; Manzano-García, S.; Alonso, R.S.; Casado-Vara, R.; Tejedor, J.P.; Prieta, F.d.l.; Rodríguez-González, S.; Parra-Domínguez, J.; Mohamad, M.S.; Trabelsi, S.; Díaz-Plaza, E.; Garcia-Coria, J.A.; Yigitcanlar, T.; Novais, P.; Omatu, S. Deepint.net: A Rapid Deployment Platform for Smart Territories. Sensors 2021, 21, 236. https://doi.org/10.3390/s210102361424-822010.3390/s21010236334014681https://www.mdpi.com/1424-8220/21/1/236info: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:RCAAP2023-07-21T12:13:55Zoai:repositorium.sdum.uminho.pt:1822/71925Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:06:06.655052Repositório 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 |
Deepint.net: A rapid deployment platform for smart territories |
title |
Deepint.net: A rapid deployment platform for smart territories |
spellingShingle |
Deepint.net: A rapid deployment platform for smart territories Corchado, Juan M. smart cities smart cyberphysical platform data analysis data visualization edge computing artificial intelligence bike renting Ciências Naturais::Ciências da Computação e da Informação Science & Technology |
title_short |
Deepint.net: A rapid deployment platform for smart territories |
title_full |
Deepint.net: A rapid deployment platform for smart territories |
title_fullStr |
Deepint.net: A rapid deployment platform for smart territories |
title_full_unstemmed |
Deepint.net: A rapid deployment platform for smart territories |
title_sort |
Deepint.net: A rapid deployment platform for smart territories |
author |
Corchado, Juan M. |
author_facet |
Corchado, Juan M. Chamoso, Pablo Hernández, Guillermo Gutierrez, Agustín San Roman Camacho, Alberto Rivas González-Briones, Alfonso Pinto-Santos, Francisco Goyenechea, Enrique Garcia-Retuerta, David Alonso-Miguel, María Hernandez, Beatriz Bellido Villaverde, Diego Valdeolmillos Sanchez-Verdejo, Manuel Plaza-Martínez, Pablo López-Pérez, Manuel Manzano-García, Sergio Alonso, Ricardo S. Casado-Vara, Roberto Tejedor, Javier Prieto Prieta, Fernando de la Rodríguez-González, Sara Parra-Domínguez, Javier Mohamad, Mohd Saberi Trabelsi, Saber Díaz-Plaza, Enrique Garcia-Coria, Jose Alberto Yigitcanlar, Tan Novais, Paulo Omatu, Sigeru |
author_role |
author |
author2 |
Chamoso, Pablo Hernández, Guillermo Gutierrez, Agustín San Roman Camacho, Alberto Rivas González-Briones, Alfonso Pinto-Santos, Francisco Goyenechea, Enrique Garcia-Retuerta, David Alonso-Miguel, María Hernandez, Beatriz Bellido Villaverde, Diego Valdeolmillos Sanchez-Verdejo, Manuel Plaza-Martínez, Pablo López-Pérez, Manuel Manzano-García, Sergio Alonso, Ricardo S. Casado-Vara, Roberto Tejedor, Javier Prieto Prieta, Fernando de la Rodríguez-González, Sara Parra-Domínguez, Javier Mohamad, Mohd Saberi Trabelsi, Saber Díaz-Plaza, Enrique Garcia-Coria, Jose Alberto Yigitcanlar, Tan Novais, Paulo Omatu, Sigeru |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Corchado, Juan M. Chamoso, Pablo Hernández, Guillermo Gutierrez, Agustín San Roman Camacho, Alberto Rivas González-Briones, Alfonso Pinto-Santos, Francisco Goyenechea, Enrique Garcia-Retuerta, David Alonso-Miguel, María Hernandez, Beatriz Bellido Villaverde, Diego Valdeolmillos Sanchez-Verdejo, Manuel Plaza-Martínez, Pablo López-Pérez, Manuel Manzano-García, Sergio Alonso, Ricardo S. Casado-Vara, Roberto Tejedor, Javier Prieto Prieta, Fernando de la Rodríguez-González, Sara Parra-Domínguez, Javier Mohamad, Mohd Saberi Trabelsi, Saber Díaz-Plaza, Enrique Garcia-Coria, Jose Alberto Yigitcanlar, Tan Novais, Paulo Omatu, Sigeru |
dc.subject.por.fl_str_mv |
smart cities smart cyberphysical platform data analysis data visualization edge computing artificial intelligence bike renting Ciências Naturais::Ciências da Computação e da Informação Science & Technology |
topic |
smart cities smart cyberphysical platform data analysis data visualization edge computing artificial intelligence bike renting Ciências Naturais::Ciências da Computação e da Informação Science & Technology |
description |
This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021-01-01T00:00:00Z |
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 |
http://hdl.handle.net/1822/71925 |
url |
http://hdl.handle.net/1822/71925 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Corchado, J.M.; Chamoso, P.; Hernández, G.; Gutierrez, A.S.R.; Camacho, A.R.; González-Briones, A.; Pinto-Santos, F.; Goyenechea, E.; Garcia-Retuerta, D.; Alonso-Miguel, M.; Hernandez, B.B.; Villaverde, D.V.; Sanchez-Verdejo, M.; Plaza-Martínez, P.; López-Pérez, M.; Manzano-García, S.; Alonso, R.S.; Casado-Vara, R.; Tejedor, J.P.; Prieta, F.d.l.; Rodríguez-González, S.; Parra-Domínguez, J.; Mohamad, M.S.; Trabelsi, S.; Díaz-Plaza, E.; Garcia-Coria, J.A.; Yigitcanlar, T.; Novais, P.; Omatu, S. Deepint.net: A Rapid Deployment Platform for Smart Territories. Sensors 2021, 21, 236. https://doi.org/10.3390/s21010236 1424-8220 10.3390/s21010236 33401468 1 https://www.mdpi.com/1424-8220/21/1/236 |
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 |
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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 |
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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) |
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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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1799132475242315776 |