Applying Classifiers in Indoor Location System

Villarrubia González, Gabriel; Rubio, Francisco; De Paz, Juan F.; Bajo Pérez, Javier; Zato Domínguez, Davinia Carolina

Título

dc.contributor.author	Villarrubia González, Gabriel
dc.contributor.author	Rubio, Francisco
dc.contributor.author	De Paz, Juan F.
dc.contributor.author	Bajo Pérez, Javier
dc.contributor.author	Zato Domínguez, Davinia Carolina
dc.date.accessioned	2017-09-06T09:17:07Z
dc.date.available	2017-09-06T09:17:07Z
dc.date.issued	2013
dc.identifier.citation	Trends in Practical Applications of Agents and Multiagent Systems Advances in Intelligent Systems and Computing. Advances in Intelligent Systems and Computing. Volumen 221, pp. 53-58.
dc.identifier.isbn	978-3-319-00562-1 (Print) / 978-3-319-00563-8 (Online)
dc.identifier.issn	2194-5357 (Print) / 2194-5365 (Online)
dc.identifier.uri	http://hdl.handle.net/10366/135158
dc.description.abstract	Research in indoor location has acquired a growing importance during the recent years. The main objective is to obtain functional systems able of providing the most precise location, identification and guidance in real time. Currently, none of the existing indoor solutions have obtained location or navigation results as precise as the ones provided by the analog systems used outdoor, such as GPS. This paper presents an indoor location system based on Wi-Fi technology which, from the use of intensity maps and classifiers, allows effective and precise indoor location.
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.publisher	Springer Science + Business Media
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject	Computer Science
dc.title	Applying Classifiers in Indoor Location System
dc.type	info:eu-repo/semantics/conferenceObject
dc.rights.accessRights	info:eu-repo/semantics/openAccess