Let’s Talk about k-NN for Indoor Positioning: Myths and Facts in RF-based Fingerprinting
Impacto
Scholar |
Otros documentos de la autoría: Torres-Sospedra, Joaquín; Pendão, Cristiano; Silva, Ivo; Meneses, Filipe; Quezada Gaibor, Darwin; Montoliu Colás, Raul; Crivello, Antonino; Barsocchi, Paolo; Pérez-Navarro, Antoni; Moreira, Adriano
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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comunitat-uji-handle3:10234/146069
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10.1109/IPIN57070.2023.10332535 |
Metadatos
Título
Let’s Talk about k-NN for Indoor Positioning: Myths and Facts in RF-based FingerprintingAutoría
Fecha de publicación
2023-09-25Editor
Institute of Electrical and Electronics Engineers Inc.ISBN
9798350320114Cita bibliográfica
J. Torres-Sospedra et al., "Let’s Talk about k-NN for Indoor Positioning: Myths and Facts in RF-based Fingerprinting," 2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nuremberg, Germany, 2023, pp. 1-6, doi: 10.1109/IPIN57070.2023.10332535.Tipo de documento
info:eu-repo/semantics/conferenceObjectVersión de la editorial
https://ieeexplore.ieee.org/abstract/document/10332535Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Microsoft proposed RADAR in 2000, the first indoor positioning system based on Wi-Fi fingerprinting. Since then, the indoor research community has worked not only to improve the base estimator but also on finding an ... [+]
Microsoft proposed RADAR in 2000, the first indoor positioning system based on Wi-Fi fingerprinting. Since then, the indoor research community has worked not only to improve the base estimator but also on finding an optimal RSS data representation. The long-term objective is to find a positioning system that minimises the mean positioning error. Despite the relevant advances in the last 23 years, a disruptive solution has not been reached yet. The evaluation with non-open datasets and comparisons with non-optimized baselines make the analysis of the current status of fingerprinting for indoor positioning difficult. In addition, the lack of implementation details or data used for evaluation in several works make results reproducibility impossible. This paper focuses on providing a comprehensive analysis of fingerprinting with k-NN and settling the basement for replicability and reproducibility in further works, targeting to bring relevant information about k-NN when it is used as a baseline comparison of advanced fingerprint-based methods. [-]
Publicado en
13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nuremberg, Germany, 2023Entidad financiadora
Fundação para a Ciência e a Tecnologia
Código del proyecto o subvención
PID2021-122642OB-C42, PID2021-122642OB-C44, UIDB/00319/2020