Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/46108

TitleA realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competition
Author(s)Torres-Sospedra, Joaquín
Moreira, Adriano
Knauth, Stefan
Berkvens, Rafael
Montoliu, Raul
Belmonte, Oscar
Trilles, Sergio
Nicolau, Maria João
Meneses, Filipe
Costa, António
Koukofikis, Athanasios
Weyn, Maarten
Peremans, Herbert
KeywordsWi-Fi Fingerprinting
Off-site competition
Indoor positioning
Issue date2017
PublisherIOS Press
JournalJournal of Ambient Intelligence and Smart Environments
CitationJoaquín Torres-Sospedra, Adriano Moreira, Stefan Knauth, Rafael Berkvens, Raul Montoliu, Oscar Belmonte, Sergio Trilles, Maria João Nicolau, Filipe Meneses, António Costa, Athanasios Koukofikis, Maarten Weyn and Herbert Peremans, “A Realistic Evaluation of Indoor Positioning Systems Based on Wi-Fi Fingerprinting: The 2015 EvAAL-ETRI Competition”, in the Journal of Ambient Intelligence and Smart Environments, 2017.
Abstract(s)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.
TypeArticle
DescriptionPre-print version
URIhttp://hdl.handle.net/1822/46108
DOI10.3233/AIS-170421
ISSN1876-1372
1876-1364
Publisher versionhttp://content.iospress.com/articles/journal-of-ambient-intelligence-and-smart-environments/ais421
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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