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Sistema de posicionamiento en interiores utilizando señales de radio estaciones FM comerciales y Deep Learning

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Sistema de posicionamiento en interiores utilizando señales de radio estaciones FM comerciales y Deep Learning

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dc.contributor.author Roman, J. es_ES
dc.contributor.author Marquez-Viloria, D. es_ES
dc.contributor.author Velásquez, R. A. es_ES
dc.contributor.author Botero-Valencia, J. es_ES
dc.date.accessioned 2020-03-04T08:20:34Z
dc.date.available 2020-03-04T08:20:34Z
dc.date.issued 2020-01-01
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/138318
dc.description.abstract [ES] Para dar solución al problema de posicionamiento en interiores, muchos autores han propuesto el uso de diversas técnicas. Desde la simulación de un Sistema de Posicionamiento Global (GPS) a través de antenas Pseudolites, la construcción de campos magnéticos artificiales, el uso de diversos sensores como visión, ultrasonido, unidades de medida inercial, entre otros. Hasta el uso de transmisores y receptores en el rango de la Radio Frecuencia como los presentes en una oficina. Muchos de los sistemas anteriormente mencionados dependen para su correcto funcionamiento de una instalación y configuración de equipos en el lugar de posicionamiento, lo cual puede llevar en ocasiones a costosas implementaciones. Es por esto que para realizar este trabajo hemos propuesto una metodología de posicionamiento en interiores que no requiere de adecuaciones e instalaciones en el lugar de aplicación. La metodología propuesta hace uso de las radio estaciones FM existentes y utiliza algoritmos de Deep Learn es_ES
dc.description.abstract [EN] For the problem of indoor positioning, many authors have proposed the use of diverses techniques. From the simulation of a Global Positioning System (GPS) through Pseudolite antennas, the construction of artificial magnetic fields, the use of various sensors such as vision, ultrasound, inertial measurement units, among others. Up to the use of transmitters and receivers in the range of Radio Frequency as those present in an oce. Many of the aforementioned systems depend for their correct operation of an installation and configuration of equipment in the place of positioning, which can sometimes lead to costly implementations. That is why to carry out this work we have proposed a indoors positioning methodology that does not require adjustments and installations in the place of application. The proposed methodology makes use of the existing FM radio stations and uses Deep Learning algorithms as positioning algorithm. es_ES
dc.description.sponsorship Grupo de investigación AECC (COL0053581) del Instituto Tecnológico Metropolitano, proyecto P14208. es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Frequency Modulation es_ES
dc.subject Indoor es_ES
dc.subject Position Estimation es_ES
dc.subject Positioning Systems es_ES
dc.subject Radio Signals es_ES
dc.subject Estimación de la posición es_ES
dc.subject Frecuencia Modulada es_ES
dc.subject Interiores es_ES
dc.subject Señales de radio es_ES
dc.subject Sistemas de posicionamiento es_ES
dc.title Sistema de posicionamiento en interiores utilizando señales de radio estaciones FM comerciales y Deep Learning es_ES
dc.title.alternative Indoor Positioning System Using FM Radio Stations Signals and Deep Learning es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2019.10894
dc.relation.projectID info:eu-repo/grantAgreement/ITM//P14208/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Roman, J.; Marquez-Viloria, D.; Velásquez, RA.; Botero-Valencia, J. (2020). Sistema de posicionamiento en interiores utilizando señales de radio estaciones FM comerciales y Deep Learning. Revista Iberoamericana de Automática e Informática industrial. 17(1):34-43. https://doi.org/10.4995/riai.2019.10894 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2019.10894 es_ES
dc.description.upvformatpinicio 34 es_ES
dc.description.upvformatpfin 43 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 17 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\10894 es_ES
dc.contributor.funder Instituto Tecnológico Metropolitano, Colombia es_ES
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