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Introducing a Human Activity Recognition Dataset Gathered on Real-Life Conditions
dc.contributor.author | García-González, Daniel | |
dc.contributor.author | Fernández-Blanco, Enrique | |
dc.contributor.author | Rivero, Daniel | |
dc.contributor.author | Rodríguez Luaces, Miguel | |
dc.date.accessioned | 2023-11-15T16:23:30Z | |
dc.date.available | 2023-11-15T16:23:30Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/2183/34246 | |
dc.description | Cursos e Congresos, C-155 | es_ES |
dc.description.abstract | [Abstract] Human activity recognition (HAR) has garnered significant scientific interest in recent years. The widespread use of smartphones enabled convenient and cost-effective data collection, eliminating the need for additional wearables. Given that, this paper introduces a novel HAR dataset in which participants had freedom in choosing smartphone orientation and placement during activities, ensuring data variability. It also includes contributions from diverse individuals, reflecting unique smartphone usage habits. Moreover, it comprises measurements from accelerometer, gyroscope, magnetometer, and GPS, corresponding to one of four activities: inactive, active, walking, or driving. Unlike other datasets, the collected data in this study were obtained from smartphones used in real-life scenarios | es_ES |
dc.description.sponsorship | This work was funded by CITIC is funded by the Xunta de Galicia through the collaboration agreement between the Consellería de Cultura, Educación, Formación Profesional e Universidades and the Galician universities for the reinforcement of the research centres of the Galician University System (CIGUS), Xunta de Galicia/FEDER-UE (ConectaPeme, GEMA: IN852A 2018/14), MINECO-AEI/FEDER-UE (Flatcity: TIN2016-77158-C4-3-R) and Xunta de Galicia/FEDER-UE (AXUDAS PARA A CONSOLIDACION E ESTRUTURACION DE UNIDADES DE INVESTIGACION COMPETITIVAS.GRC: ED431C 2017/58 and ED431C 2018/49). | |
dc.description.sponsorship | Xunta de Galicia; ED431C 2017/58 | |
dc.description.sponsorship | Xunta de Galicia; ED431C 2018/49 | |
dc.language.iso | eng | es_ES |
dc.publisher | Universidade da Coruña, Servizo de Publicacións | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2016-77158-C4-3-R/ES/VELOCITY: PROCESADO EFICIENTE DE BIG DATA ESPAZO-TEMPORAL PARA FLATCITY | |
dc.relation.uri | https://doi.org/10.17979/spudc.000024.08 | |
dc.rights | Attribution 4.0 International (CC BY 4.0) | es_ES |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/deed.es | * |
dc.subject | Datos HAR | es_ES |
dc.subject | Smartphones | es_ES |
dc.subject | Dispositivos móviles | es_ES |
dc.title | Introducing a Human Activity Recognition Dataset Gathered on Real-Life Conditions | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.startPage | 47 | es_ES |
UDC.endPage | 54 | es_ES |
UDC.conferenceTitle | VI Congreso Xove TIC: impulsando el talento científico. Octubre, 2023, A Coruña | es_ES |