Ubiquitous sensorization for multimodal assessment of driving patterns

Detalhes bibliográficos
Autor(a) principal: Silva, Fábio
Data de Publicação: 2014
Outros Autores: Analide, Cesar, Gonçalves, Celestino, Sarmento, João
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/1822/36529
Resumo: Sustainability issues and sustainable behaviours are becoming concerns of increasing signi cance in our society. In the case of transportation systems, it would be important to know the impact of a given driving behaviour over sustainability factors. This paper describes a system that integrates ubiquitous mobile sensors available on devices such as smartphones, intelligent wristbands and smartwatches, in order to determine and classify driving patterns and to assess driving e ficiency and driver's moods. It first identi fies the main attributes for contextual information, with relevance to driving analysis. Next, it describes how to obtain that information from ubiquitous mobile sensors, usually carried by drivers. Finally, it addresses the multimodal assessment process which produces the analysis of driving patterns and the classi cation of driving moods, promoting the identifi cation of either regular or aggressive driving patterns, and the classi fication of mood types between aggressive and relaxed. Such an approach enables ubiquitous sensing of personal driving patterns across diff erent vehicles, which can be used in sustainability frameworks, driving alerts and recommendation systems.
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spelling Ubiquitous sensorization for multimodal assessment of driving patternsDriving ProfileMobile SensorsSustainabilityCiências Naturais::Ciências da Computação e da InformaçãoEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaSustainability issues and sustainable behaviours are becoming concerns of increasing signi cance in our society. In the case of transportation systems, it would be important to know the impact of a given driving behaviour over sustainability factors. This paper describes a system that integrates ubiquitous mobile sensors available on devices such as smartphones, intelligent wristbands and smartwatches, in order to determine and classify driving patterns and to assess driving e ficiency and driver's moods. It first identi fies the main attributes for contextual information, with relevance to driving analysis. Next, it describes how to obtain that information from ubiquitous mobile sensors, usually carried by drivers. Finally, it addresses the multimodal assessment process which produces the analysis of driving patterns and the classi cation of driving moods, promoting the identifi cation of either regular or aggressive driving patterns, and the classi fication of mood types between aggressive and relaxed. Such an approach enables ubiquitous sensing of personal driving patterns across diff erent vehicles, which can be used in sustainability frameworks, driving alerts and recommendation systems.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). It is also supported by a doctoral grant, SFRH/BD/78713/2011, issued by FCT in Portugal.Springer VerlagUniversidade do MinhoSilva, FábioAnalide, CesarGonçalves, CelestinoSarmento, João2014-052014-05-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/36529engSilva, F., Analide, C., Gonçalves, C., Sarmento, J., Ubiquitous Sensorization for Multimodal Assessment of Driving Patterns, Ambient Intelligence - Software and Applications, 5th International Symposium on Ambient Intelligence, pp 143-150, 2014, ISBN 978-3-319-07595-2, ISSN 978-3-319-07596-9, Advances in Intelligent Systems and Computing, vol. 291, eds. Ramos, C., Novais, P., Nihan, C., Corchado, J.M., Springer International Publishing978-3-319-07595-22194-535710.1007/978-3-319-07596-9_16info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:37:46Zoai:repositorium.sdum.uminho.pt:1822/36529Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:34:06.616607Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Ubiquitous sensorization for multimodal assessment of driving patterns
title Ubiquitous sensorization for multimodal assessment of driving patterns
spellingShingle Ubiquitous sensorization for multimodal assessment of driving patterns
Silva, Fábio
Driving Profile
Mobile Sensors
Sustainability
Ciências Naturais::Ciências da Computação e da Informação
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
title_short Ubiquitous sensorization for multimodal assessment of driving patterns
title_full Ubiquitous sensorization for multimodal assessment of driving patterns
title_fullStr Ubiquitous sensorization for multimodal assessment of driving patterns
title_full_unstemmed Ubiquitous sensorization for multimodal assessment of driving patterns
title_sort Ubiquitous sensorization for multimodal assessment of driving patterns
author Silva, Fábio
author_facet Silva, Fábio
Analide, Cesar
Gonçalves, Celestino
Sarmento, João
author_role author
author2 Analide, Cesar
Gonçalves, Celestino
Sarmento, João
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Silva, Fábio
Analide, Cesar
Gonçalves, Celestino
Sarmento, João
dc.subject.por.fl_str_mv Driving Profile
Mobile Sensors
Sustainability
Ciências Naturais::Ciências da Computação e da Informação
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
topic Driving Profile
Mobile Sensors
Sustainability
Ciências Naturais::Ciências da Computação e da Informação
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
description Sustainability issues and sustainable behaviours are becoming concerns of increasing signi cance in our society. In the case of transportation systems, it would be important to know the impact of a given driving behaviour over sustainability factors. This paper describes a system that integrates ubiquitous mobile sensors available on devices such as smartphones, intelligent wristbands and smartwatches, in order to determine and classify driving patterns and to assess driving e ficiency and driver's moods. It first identi fies the main attributes for contextual information, with relevance to driving analysis. Next, it describes how to obtain that information from ubiquitous mobile sensors, usually carried by drivers. Finally, it addresses the multimodal assessment process which produces the analysis of driving patterns and the classi cation of driving moods, promoting the identifi cation of either regular or aggressive driving patterns, and the classi fication of mood types between aggressive and relaxed. Such an approach enables ubiquitous sensing of personal driving patterns across diff erent vehicles, which can be used in sustainability frameworks, driving alerts and recommendation systems.
publishDate 2014
dc.date.none.fl_str_mv 2014-05
2014-05-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/36529
url http://hdl.handle.net/1822/36529
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Silva, F., Analide, C., Gonçalves, C., Sarmento, J., Ubiquitous Sensorization for Multimodal Assessment of Driving Patterns, Ambient Intelligence - Software and Applications, 5th International Symposium on Ambient Intelligence, pp 143-150, 2014, ISBN 978-3-319-07595-2, ISSN 978-3-319-07596-9, Advances in Intelligent Systems and Computing, vol. 291, eds. Ramos, C., Novais, P., Nihan, C., Corchado, J.M., Springer International Publishing
978-3-319-07595-2
2194-5357
10.1007/978-3-319-07596-9_16
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 Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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