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dc.contributor.authorPrieto Tejedor, Javier 
dc.contributor.authorPaz Santana, Juan Francisco de 
dc.contributor.authorVillarrubia González, Gabriel 
dc.contributor.authorBajo Pérez, Javier
dc.contributor.authorCorchado Rodríguez, Juan Manuel
dc.identifier.citationAmbient Intelligence- Software and Applications – 6th International Symposium on Ambient Intelligence (ISAmI 2015). Advances in Intelligent Systems and Computing. pp. 223-231.
dc.identifier.isbn978-3-319-19694-7(Print) / 978-3-319-19695-4(Online)
dc.identifier.issn2194-5357(Print) / 2194-5365(Online)
dc.description.abstractIndoor localization constitutes one of the main pillars for the provision of context-aware services in e-Healthcare systems. Fingerprinting and ranging have traditionally been placed facing each other to meet the localization requirements. However, accurate fingerprinting may worth the exhaustive calibration effort in some critical areas while easy-to-deploy ranging can provide adequate accuracy for certain non-critical spaces. In this paper, we propose a framework and algorithm for seamless integration of both systems from the Bayesian perspective. We assessed the proposed framework with conventional WiFi devices in comparison to conventional implementations. The presented techniques exhibit a remarkable accuracy improvement while they avoid computationally exhaustive algorithms that impede real-time operation.
dc.publisherAmr Mahmoud Salem Mohamed, Paulo Novais, Antonio Pereira, Villarrubia González, Gabriel, Antonio Fernández-Caballero (Eds.). Springer Verlag.
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.subjectComputer Science
dc.titleUnified Fingerprinting/Ranging Localization for e-Healthcare Systems

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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported