A radiosity-based method to avoid calibration for Indoor Positioning Systems
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Otros documentos de la autoría: Belmonte-Fernández, Óscar; Montoliu Colás, Raul; Torres-Sospedra, Joaquín; Sansano-Sansano, Emilio; Chia-Aguilar, Daniel
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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INVESTIGACIONMetadatos
Título
A radiosity-based method to avoid calibration for Indoor Positioning SystemsAutoría
Fecha de publicación
2018-09-01Editor
ElsevierCita bibliográfica
BELMONTE FERNÁNDEZ, Óscar; MONTOLIU COLÁS, Raúl; TORRES-SOSPEDRA, Joaquín; SANSANO-SANSANO, Emilio; CHIA-AGUILAR, Daniel (2018). A radiosity-based method to avoid calibration for indoor positioning systems. Expert Systems with Applications, v. 105, p. 89-101Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/pii/S0957417418302112Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Due to the widespread use of mobile devices, services based on the users current indoor location are growing in significance. Such services are developed in the Machine Learning and Experst Systems realm, and ranges ... [+]
Due to the widespread use of mobile devices, services based on the users current indoor location are growing in significance. Such services are developed in the Machine Learning and Experst Systems realm, and ranges from guidance for blind people to mobile tourism and indoor shopping. One of the most used techniques for indoor positioning is WiFi fingerprinting, being its use of widespread WiFi signals one of the main reasons for its popularity, mostly on high populated urban areas. Most issues of this approach rely on the data acquisition phase; to manually sample WiFi RSSI signals in order to create a WiFi radio map is a high time consuming task, also subject to re-calibrations, because any change in the environment might affect the signal propagation, and therefore degrade the performance of the positioning system. The work presented in this paper aims at substituting the manual data acquisition phase by directly calculating the WiFi radio map by means of a radiosity signal propagation model. The time needed to acquire the WiFi radio map by means of the radiosity model dramatically reduces from hours to minutes when compared with manual acquisition. The proposed method is able to produce competitive results, in terms of accuracy, when compared with manual sampling, which can help domain experts develop services based on location faster. [-]
Publicado en
Expert Systems with Applications (2018), v. 105Proyecto de investigación
1) Spanish Ministry of Economy and Competitiveness through the “Proyectos I + D Excelencia” programme 620 (TIN2015-70202-P) and 2) Jaume I University “Research promotion plan 2017” programme (UJI-B2017-45).Derechos de acceso
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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