Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/70550
Título: | Exploiting different combinations of complementary sensor's data for fingerprint-based indoor positioning in industrial environments |
Autor(es): | Torres-Sospedra, Joaquín Moreira, Adriano Mendoza-Silva, German M. Nicolau, Maria João Matey-Sanz, Miguel Silva, Ivo Miguel Menezes Huerta, Joaquin Pendão, Cristiano Gonçalves |
Palavras-chave: | Autonomous vehicle Ensemble models Indoor positioning Multiple interfaces RSSI Wi-Fi fingerprinting |
Data: | 2019 |
Editora: | Institute of Electrical and Electronics Engineers Inc. |
Revista: | International Conference on Indoor Positioning and Indoor Navigation |
Citação: | J. Torres-Sospedra et al., "Exploiting Different Combinations of Complementary Sensor’s data for Fingerprint-based Indoor Positioning in Industrial Environments," 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Pisa, Italy, 2019, pp. 1-8, doi: 10.1109/IPIN.2019.8911758 |
Resumo(s): | Wi-Fi fingerprinting is a popular technique for smartphone-based indoor positioning. However, well-known RF propagation issues create signal fluctuations that translate into large positioning errors. Large errors limit the usage of Wi-Fi fingerprinting in industrial environments, where the reliability of position estimates is a key requirement. One successful approach to deal with signal fluctuations is to average the signals collected simultaneously through independent Wi-Fi interfaces. Another successful approach is to average the estimates provided by models built on independent radio maps. This paper explores multiple combinations of both approaches and determines the procedure to select the best model based on them through a simulated environment. The evaluation of the proposed model in a real-world industrial scenario shows that the positioning error (according to different metrics including the 95th and 99th percentiles) is highly improved with respect to the traditional fingerprint. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/70550 |
ISBN: | 9781728117881 |
DOI: | 10.1109/IPIN.2019.8911758 |
ISSN: | 2162-7347 |
Versão da editora: | https://ieeexplore.ieee.org/document/8911758 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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08911758.pdf Acesso restrito! | 501,75 kB | Adobe PDF | Ver/Abrir |