Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/51539
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Campo DC | Valor | Idioma |
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dc.contributor.author | Anacleto, Ricardo | por |
dc.contributor.author | Figueiredo, Lino | por |
dc.contributor.author | Almeida, Ana | por |
dc.contributor.author | Novais, Paulo | por |
dc.contributor.author | Meireles, António | por |
dc.date.accessioned | 2018-03-05T15:01:15Z | - |
dc.date.available | 2018-03-05T15:01:15Z | - |
dc.date.issued | 2015 | - |
dc.identifier.isbn | 978-3-319-19694-7 | - |
dc.identifier.issn | 2194-5357 | - |
dc.identifier.uri | https://hdl.handle.net/1822/51539 | - |
dc.description.abstract | In order to suppress the GNSS (Global Navigation Satellite System) limitation to track persons in indoor or in dense environments, a pedestrian inertial navigation system can be used. However, this type of systems have huge location estimation errors due to the Pedestrian Dead Reckoning (PDR) characteristics and the use of low-cost inertial sensors. To suppress some of these errors we propose a system that uses several sensors spread in person's body combined with information fusion techniques. Information fusion techniques provide lighter algorithms implementations, to count and classify the type of step, to run in mobile devices. Thus, improving pedestrian inertial navigation systems accuracy. | por |
dc.description.sponsorship | 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). Ricardo also acknowledge FCT for the support of his work through the PhD grant SFRH/DB/70248/2010. | por |
dc.language.iso | eng | por |
dc.publisher | Springer | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876-PPCDTI/126449/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/COMPETE/126449/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F70248%2F2010/PT | por |
dc.rights | openAccess | por |
dc.subject | Pedestrian Inertial Navigation System | por |
dc.subject | Step Count | por |
dc.subject | Information Fusion | por |
dc.subject | Dynamic Time Warping | por |
dc.title | Step count and classification using sensor information fusion | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
oaire.citationStartPage | 85 | por |
oaire.citationEndPage | 93 | por |
oaire.citationVolume | 376 | por |
dc.date.updated | 2018-02-15T11:53:53Z | - |
dc.identifier.eissn | 2194-5365 | - |
dc.identifier.doi | 10.1007/978-3-319-19695-4_9 | por |
dc.identifier.eisbn | 978-3-319-19695-4 | - |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | por |
sdum.export.identifier | 2751 | - |
sdum.journal | Advances in Intelligent Systems and Computing | por |
sdum.conferencePublication | Ambient intelligence - software and applications: proceedings of the 6th International Symposium on Ambient Intelligence (ISAmI 2015) | por |
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Ficheiro | Descrição | Tamanho | Formato | |
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step.count.classification.sensor.information.fusion.pdf | 2,16 MB | Adobe PDF | Ver/Abrir |