Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/41884
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dc.contributor.authorAlonso-González, Itziaren_US
dc.contributor.authorSanchez-Rodriguez, Daviden_US
dc.contributor.authorLey-Bosch, Carlosen_US
dc.contributor.authorQuintana-Suarez, Miguel A.en_US
dc.date.accessioned2018-09-07T10:09:46Z-
dc.date.available2018-09-07T10:09:46Z-
dc.date.issued2018en_US
dc.identifier.issn1424-8220en_US
dc.identifier.urihttp://hdl.handle.net/10553/41884-
dc.description.abstractIndoor localization estimation has become an attractive research topic due to growing interest in location-aware services. Many research works have proposed solving this problem by using wireless communication systems based on radiofrequency. Nevertheless, those approaches usually deliver an accuracy of up to two metres, since they are hindered by multipath propagation. On the other hand, in the last few years, the increasing use of light-emitting diodes in illumination systems has provided the emergence of Visible Light Communication technologies, in which data communication is performed by transmitting through the visible band of the electromagnetic spectrum. This brings a brand new approach to high accuracy indoor positioning because this kind of network is not affected by electromagnetic interferences and the received optical power is more stable than radio signals. Our research focus on to propose a fingerprinting indoor positioning estimation system based on neural networks to predict the device position in a 3D environment. Neural networks are an effective classification and predictive method. The localization system is built using a dataset of received signal strength coming from a grid of different points. From the these values, the position in Cartesian coordinates (x, y, z) is estimated. The use of three neural networks is proposed in this work, where each network is responsible for estimating the position by each axis. Experimental results indicate that the proposed system leads to substantial improvements to accuracy over the widely-used traditional fingerprinting methods, yielding an accuracy above 99% and an average error distance of 0.4 mm.en_US
dc.languageengen_US
dc.publisher1424-8220
dc.relation.ispartofSensorsen_US
dc.sourceSensors [ISSN 1424-8220], v. 18 (4), 1040en_US
dc.subject3325 Tecnología de las telecomunicacionesen_US
dc.subject3307 Tecnología electrónicaen_US
dc.subject.otherIndoor localizationen_US
dc.subject.otherNeural networken_US
dc.subject.otherVisible light communicationen_US
dc.subject.otherReceived signal strengthen_US
dc.titleDiscrete Indoor three-dimensional localization system based on neural networks using visible light communicationen_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.3390/s18041040
dc.identifier.scopus85044971975
dc.identifier.isi000435574800112-
dc.contributor.authorscopusid56690273300
dc.contributor.authorscopusid56690271600
dc.contributor.authorscopusid16175642300
dc.contributor.authorscopusid56997469700
dc.identifier.issue4-
dc.description.firstpage1040-
dc.relation.volume18-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid3636243
dc.contributor.daisngid3316951
dc.contributor.daisngid5430958
dc.contributor.daisngid7318980
dc.contributor.wosstandardWOS:Alonso-Gonzalez, I
dc.contributor.wosstandardWOS:Sanchez-Rodriguez, D
dc.contributor.wosstandardWOS:Ley-Bosch, C
dc.contributor.wosstandardWOS:Quintana-Suarez, MA
dc.date.coverdateAbril 2018
dc.identifier.ulpgces
dc.description.sjr0,592
dc.description.jcr3,031
dc.description.sjrqQ2
dc.description.jcrqQ2
dc.description.scieSCIE
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR IDeTIC: División de Redes y Servicios Telemáticos-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Ingeniería Telemática-
crisitem.author.deptGIR IDeTIC: División de Redes y Servicios Telemáticos-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Ingeniería Telemática-
crisitem.author.deptGIR IDeTIC: División de Redes y Servicios Telemáticos-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Ingeniería Telemática-
crisitem.author.deptDepartamento de Ingeniería Telemática-
crisitem.author.orcid0000-0001-8487-2559-
crisitem.author.orcid0000-0003-2700-1591-
crisitem.author.orcid0000-0002-0939-3045-
crisitem.author.orcid0000-0002-7520-4468-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameAlonso González, Itziar Goretti-
crisitem.author.fullNameSánchez Rodríguez, David De La Cruz-
crisitem.author.fullNameLey Bosch, Carlos-
crisitem.author.fullNameQuintana Suárez, Miguel Ángel-
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