Lightweight Wi-Fi Fingerprinting with a Novel RSS Clustering Algorithm

Darwin Quezada-Gaibor, Joaquín Torres-Sospedra, Jari Nurmi, Yevgeny Koucheryavy, Joaquin Huerta

Tutkimustuotos: KonferenssiartikkeliTieteellinenvertaisarvioitu

7 Sitaatiot (Scopus)
31 Lataukset (Pure)

Abstrakti

Nowadays, several indoor positioning solutions sup-port Wi-Fi and use this technology to estimate the user position. It is characterized by its low cost, availability in indoor and outdoor environments, and a wide variety of devices support Wi-Fi technology. However, this technique suffers from scalability problems when the radio map has a large number of reference fingerprints because this might increase the time response in the operational phase. In order to minimize the time response, many solutions have been proposed along the time. The most common solution is to divide the data set into clusters. Thus, the incoming fingerprint will be compared with a specific number of samples grouped by, for instance similarity (clusters). Many of the current studies have proposed a variety of solutions based on the modification of traditional clustering algorithms in order to provide a better distribution of samples and reduce the computational load. This work proposes a new clustering method based on the maximum Received Signal Strength (RSS) values to join similar fingerprints. As a result, the proposed fingerprinting clustering method outperforms three of the most well-known clustering algorithms in terms of processing time at the operational phase of fingerprinting.
AlkuperäiskieliEnglanti
Otsikko2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
KustantajaIEEE
Sivut1-8
Sivumäärä8
ISBN (elektroninen)978-1-6654-0402-0
DOI - pysyväislinkit
TilaJulkaistu - 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Indoor Positioning and Indoor Navigation - , Espanja
Kesto: 29 marrask. 20212 jouluk. 2021

Julkaisusarja

NimiInternational Conference on Indoor Positioning and Indoor Navigation
ISSN (elektroninen)2471-917X

Conference

ConferenceInternational Conference on Indoor Positioning and Indoor Navigation
Maa/AlueEspanja
Ajanjakso29/11/212/12/21

Julkaisufoorumi-taso

  • Jufo-taso 1

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