A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competition
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Altres documents de l'autoria: Torres-Sospedra, Joaquín; Moreira, Adriano; Knauth, Stefan; Berkvens, Rafael; Montoliu Colás, Raul; Belmonte-Fernández, Óscar; Trilles, Sergio; Nicolau, Maria João; Meneses, Filipe; Costa, António; Koukofikis, Athanasios; Weyn, Maarten; Peremans, Herbert
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Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/8634
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Títol
A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competitionAutoria
Data de publicació
2017-02Editor
IOS pressCita bibliogràfica
TORRES-SOSPEDRA, Joaquín, et al. A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competition. Journal of Ambient Intelligence and Smart Environments, 2017, vol. 9, no 2, p. 263-279.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
http://content.iospress.com/articles/journal-of-ambient-intelligence-and-smart-e ...Versió
info:eu-repo/semantics/submittedVersionParaules clau / Matèries
Resum
This paper presents results from comparing different Wi-Fi fingerprinting algorithms on the same private dataset. The algorithms where realized by independent teams in the frame of the off-site track of the EvAAL–ETRI ... [+]
This paper presents results from comparing different Wi-Fi fingerprinting algorithms on the same private dataset. The algorithms where realized by independent teams in the frame of the off-site track of the EvAAL–ETRI Indoor Localization Competition which was part of the Sixth International Conference on Indoor Positioning and Indoor Navigation (IPIN 2015). Competitors designed and validated their algorithms against the publicly available UJIIndoorLoc database which contains a huge reference- and validation data set. All competing systems were evaluated using the mean error in positioning, with penalties, using a private test dataset. The authors believe that this is the first work in which Wi-Fi fingerprinting algorithm results delivered by several independent and competing teams are fairly compared under the same evaluation conditions. The analysis also comprises a combined approach: Results indicate that the competing systems where complementary, since an ensemble that combines three competing methods reported the overall best results. [-]
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Journal of Ambient Intelligence and Smart Environments, 2017, vol. 9, no 2Drets d'accés
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