Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43560
DC FieldValueLanguage
dc.contributor.authorPadrón, Gabinoen_US
dc.contributor.authorAlayón, Franciscoen_US
dc.contributor.authorCristóbal, Teresaen_US
dc.contributor.authorQuesada-Arencibia, Alexisen_US
dc.contributor.authorGarcía, Carmelo R.en_US
dc.contributor.otherQuesada-Arencibia, Alexis-
dc.contributor.otherQuesada-Arencibia, Alexis-
dc.date.accessioned2018-11-21T16:08:07Z-
dc.date.available2018-11-21T16:08:07Z-
dc.date.issued2016en_US
dc.identifier.isbn978-3-319-48798-4en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10553/43560-
dc.description.abstractNowadays the public transport systems play a main role in the advanced societies. How to evaluate the quality of the public transport is a critic task of the transport regulatory agencies. One indicator used to measure this quality is the fulfilment of the scheduled operation by the transport operators, specially scheduled arrival times and frequencies at stops. In this paper, an automatic system to estimate arrival times in the context of road public transport is proposed. The system works autonomously, acquiring massive vehicle position readings, registering and processing them automatically in order to estimate arrival times. This autonomous behaviour is achieved using pattern recognition and statistical techniques. To illustrate the application of the system, the estimation of arrival times at a bus stop is presented.en_US
dc.languageengen_US
dc.publisherSpringeren_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceUbiquitous Computing and Ambient Intelligence. IWAAL 2016, AmIHEALTH 2016, UCAmI 2016. Lecture Notes in Computer Science, v. 10070, p. 395-406en_US
dc.subject120304 Inteligencia artificialen_US
dc.subject3327 Tecnología de los sistemas de transporteen_US
dc.subject.otherIntelligent transport systemsen_US
dc.subject.otherFloat car dataen_US
dc.subject.otherPattern recognitionen_US
dc.subject.otherArtificial intelligenceen_US
dc.subject.otherBus transportationen_US
dc.subject.otherTraffic controlen_US
dc.titleArrival time estimation system based on massive positioning data of public transport vehiclesen_US
dc.typeinfo:eu-repo/semantics/bookParten_US
dc.typebookParten_US
dc.relation.conference10th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2016)-
dc.identifier.doi10.1007/978-3-319-48799-1_44en_US
dc.identifier.scopus85009820781-
dc.identifier.isi000389507400044-
dcterms.isPartOfUbiquitous Computing And Ambient Intelligence, Ucami 2016, Pt Ii-
dcterms.sourceUbiquitous Computing And Ambient Intelligence, Ucami 2016, Pt Ii[ISSN 0302-9743],v. 10070, p. 395-406-
dc.contributor.authorscopusid22986240200-
dc.contributor.authorscopusid6506717943-
dc.contributor.authorscopusid56495304700-
dc.contributor.authorscopusid13006053800-
dc.contributor.authorscopusid7401486323-
dc.identifier.eissn1611-3349-
dc.description.lastpage406en_US
dc.description.firstpage395en_US
dc.relation.volume10070en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Capítulo de libroen_US
dc.identifier.wosWOS:000389507400044-
dc.contributor.daisngid2375619-
dc.contributor.daisngid1986574-
dc.contributor.daisngid4451412-
dc.contributor.daisngid1279635-
dc.contributor.daisngid1412377-
dc.identifier.investigatorRIDG-2656-2016-
dc.identifier.investigatorRIDG-2656-2016-
dc.identifier.externalWOS:000389507400044-
dc.identifier.eisbn978-3-319-48799-1-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Padron, G-
dc.contributor.wosstandardWOS:Alayon, F-
dc.contributor.wosstandardWOS:Cristobal, T-
dc.contributor.wosstandardWOS:Quesada-Arencibia, A-
dc.contributor.wosstandardWOS:Garcia, CR-
dc.date.coverdateEnero 2016en_US
dc.identifier.supplement0302-9743-
dc.identifier.supplement0302-9743-
dc.identifier.conferenceidevents121005-
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.description.sjr0,315
dc.description.sjrqQ3
dc.description.spiqQ1
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.event.eventsstartdate29-11-2016-
crisitem.event.eventsenddate02-12-2016-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-5573-1156-
crisitem.author.orcid0000-0002-7285-9194-
crisitem.author.orcid0000-0002-8313-5124-
crisitem.author.orcid0000-0003-1433-3730-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.fullNamePadrón Morales, Gabino-
crisitem.author.fullNameAlayón Hernández,Francisco Javier-
crisitem.author.fullNameQuesada Arencibia, Francisco Alexis-
crisitem.author.fullNameGarcía Rodríguez, Carmelo Rubén-
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