A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competition
View/ Open
Impact
Scholar |
Other documents of the author: 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
Metadata
Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/8634
comunitat-uji-handle4:
INVESTIGACIONMetadata
Title
A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competitionAuthor (s)
Date
2017-02Publisher
IOS pressBibliographic citation
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.Type
info:eu-repo/semantics/articlePublisher version
http://content.iospress.com/articles/journal-of-ambient-intelligence-and-smart-e ...Version
info:eu-repo/semantics/submittedVersionAbstract
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. [-]
Is part of
Journal of Ambient Intelligence and Smart Environments, 2017, vol. 9, no 2Rights
Copyright © 2017 IOS Press All rights reserved.
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
This item appears in the folowing collection(s)
- INIT_Articles [754]
- LSI_Articles [366]