Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems

Cities are becoming data-driven, re-engineering their processes to adapt to dynamically changing needs. A.I. brings new capabilities, effectively enlarging the space of policy interventions that can be explored and applied. Therefore, new tools are needed to augment our capacity to traverse this spa...

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Detalhes bibliográficos
Autores: Almirall, Esteve, Callegaro, Davide, bruins, peter, Santamaría, Mar, Martínez, Pablo, Cortés, Ulises
Tipo de documento: artigo
Data de publicação:2022
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositório:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:20.500.14342/5122
Acesso em linha:https://hdl.handle.net/20.500.14342/5122
http://doi.org/10.3233/FAIA220319
Access Level:Acceso aberto
Palavra-chave:Digital Twins
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spelling Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data ProblemsAlmirall, EsteveCallegaro, Davidebruins, peterSantamaría, MarMartínez, PabloCortés, UlisesDigital TwinsCities are becoming data-driven, re-engineering their processes to adapt to dynamically changing needs. A.I. brings new capabilities, effectively enlarging the space of policy interventions that can be explored and applied. Therefore, new tools are needed to augment our capacity to traverse this space and find adequate policy interventions. Digital twins are revealing themselves as powerful tools for policy experimentation and exploration, allowing faster and more complete explorations while avoiding costly interventions. However, they face some problems, among them data availability and model scalability. We introduce a digital twin framework based on an A.I. and a synthetic data model on NO2 pollution as a proof-of-concept, showing that this approach is feasible for policy evaluation and (autonomous) intervention and solves the problems of data scarcity and model scalability while enabling city level Open Innovation.info:eu-repo/semantics/publishedVersionIOS Press BVUniversitat Ramon Llull. Esade2022info:eu-repo/semantics/article4 p.https://hdl.handle.net/20.500.14342/5122http://doi.org/10.3233/FAIA220319reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésFrontiers in Artificial Intelligence and Applications© L'autor/aAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:20.500.14342/51222026-05-29T05:05:01Z
dc.title.none.fl_str_mv Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
title Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
spellingShingle Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
Almirall, Esteve
Digital Twins
title_short Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
title_full Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
title_fullStr Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
title_full_unstemmed Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
title_sort Deep Air – A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems
dc.creator.none.fl_str_mv Almirall, Esteve
Callegaro, Davide
bruins, peter
Santamaría, Mar
Martínez, Pablo
Cortés, Ulises
author Almirall, Esteve
author_facet Almirall, Esteve
Callegaro, Davide
bruins, peter
Santamaría, Mar
Martínez, Pablo
Cortés, Ulises
author_role author
author2 Callegaro, Davide
bruins, peter
Santamaría, Mar
Martínez, Pablo
Cortés, Ulises
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universitat Ramon Llull. Esade
dc.subject.none.fl_str_mv Digital Twins
topic Digital Twins
description Cities are becoming data-driven, re-engineering their processes to adapt to dynamically changing needs. A.I. brings new capabilities, effectively enlarging the space of policy interventions that can be explored and applied. Therefore, new tools are needed to augment our capacity to traverse this space and find adequate policy interventions. Digital twins are revealing themselves as powerful tools for policy experimentation and exploration, allowing faster and more complete explorations while avoiding costly interventions. However, they face some problems, among them data availability and model scalability. We introduce a digital twin framework based on an A.I. and a synthetic data model on NO2 pollution as a proof-of-concept, showing that this approach is feasible for policy evaluation and (autonomous) intervention and solves the problems of data scarcity and model scalability while enabling city level Open Innovation.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14342/5122
http://doi.org/10.3233/FAIA220319
url https://hdl.handle.net/20.500.14342/5122
http://doi.org/10.3233/FAIA220319
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Frontiers in Artificial Intelligence and Applications
dc.rights.none.fl_str_mv © L'autor/a
Attribution-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv © L'autor/a
Attribution-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 4 p.
dc.publisher.none.fl_str_mv IOS Press BV
publisher.none.fl_str_mv IOS Press BV
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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