Please use this identifier to cite or link to this item: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/2399
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dc.contributor299983es_ES
dc.coverage.spatialGlobales_ES
dc.creatorGalván-Tejada, Carlos Eric-
dc.date.accessioned2021-04-27T20:04:47Z-
dc.date.available2021-04-27T20:04:47Z-
dc.date.issued2013-09-16-
dc.identifierinfo:eu-repo/semantics/publishedVersiones_ES
dc.identifier.urihttp://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/2399-
dc.descriptionUser indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices. These sensory devices allow us to exploit not only infrastructures made for every day use, such as Wi-Fi, but also natural infrastructure, as is the case of natural magnetic fields. From our experience working with mobile devices and Magnetic-Field based location systems, we identify some issues that should be addressed to improve the performance of a Magnetic-Field based system, such as a reduction of the data to be analyzed to estimate an individual location. In this paper we propose a feature extraction process that uses magnetic-field temporal and spectral features to acquire a classification model using the capabilities of mobile phones. Finally, we present a comparison against well known spectral classification algorithms with the aim to ensure the reliability of the feature extraction process.es_ES
dc.description.abstractUser indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices. These sensory devices allow us to exploit not only infrastructures made for every day use, such as Wi-Fi, but also natural infrastructure, as is the case of natural magnetic fields. From our experience working with mobile devices and Magnetic-Field based location systems, we identify some issues that should be addressed to improve the performance of a Magnetic-Field based system, such as a reduction of the data to be analyzed to estimate an individual location. In this paper we propose a feature extraction process that uses magnetic-field temporal and spectral features to acquire a classification model using the capabilities of mobile phones. Finally, we present a comparison against well known spectral classification algorithms with the aim to ensure the reliability of the feature extraction process.es_ES
dc.language.isospaes_ES
dc.publisherSpringeres_ES
dc.relationhttps://link.springer.com/chapter/10.1007/978-3-319-03176-7_2es_ES
dc.relation.urigeneralPublices_ES
dc.sourcehttps://link.springer.com/chapter/10.1007/978-3-319-03176-7_2es_ES
dc.subject.classificationINGENIERIA Y TECNOLOGIA [7]es_ES
dc.subject.otherINDOOR LOCATIONes_ES
dc.subject.otherMobile deviceses_ES
dc.subject.othersensory deviceses_ES
dc.titleMagnetic-field feature extraction for indoor location estimationes_ES
dc.title.alternativeMagnetic-field feature extraction for indoor location estimationes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
Appears in Collections:*Documentos Académicos*-- M. en Ciencias del Proc. de la Info.

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