Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/70554
Título: | A comprehensive and reproducible comparison of clustering and optimization rules in Wi-Fi fingerprinting |
Autor(es): | Torres-Sospedra, Joaquín Richter, Philipp Moreira, Adriano Mendoza-Silva, Germán M. Lohan, Elena Simona Trilles, Sergio Matey-Sanz, Miguel Huerta, Joaquín |
Palavras-chave: | Indoor positioning Wi-Fi fingerprinting Clustering Computational costs Time complexity Benchmarking Reproducibility |
Data: | 2022 |
Editora: | IEEE |
Revista: | IEEE Transactions on Mobile Computing (TMC) |
Citação: | Torres-Sospedra, J., Richter, P., Moreira, A., Mendoza-Silva, G. M., Lohan, E. S., Trilles, S., … Huerta, J. (2022, March 1). A Comprehensive and Reproducible Comparison of Clustering and Optimization Rules in Wi-Fi Fingerprinting. IEEE Transactions on Mobile Computing. Institute of Electrical and Electronics Engineers (IEEE). http://doi.org/10.1109/tmc.2020.3017176 |
Resumo(s): | Wi-Fi fingerprinting is a well-known technique used for indoor positioning. It relies on a pattern recognition method that compares the captured operational fingerprint with a set of previously collected reference samples (radio map) using a similarity function. The matching algorithms suffer from a scalability problem in large deployments with a huge density of fingerprints, where the number of reference samples in the radio map is prohibitively large. This paper presents a comprehensive comparative study of existing methods to reduce the complexity and size of the radio map used at the operational stage. Our empirical results show that most of the methods reduce the computational burden at the expense of a degraded accuracy. Among the studied methods, only k-means, affinity propagation, and the rules based on the strongest access point properly balance the positioning accuracy and computational time. In addition to the comparative results, this paper also introduces a new evaluation framework with multiple datasets, aiming at getting more general results and contributing to a better reproducibility of new proposed solutions in the future. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/70554 |
DOI: | 10.1109/TMC.2020.3017176 |
ISSN: | 1536-1233 |
e-ISSN: | 1558-0660 |
Versão da editora: | https://ieeexplore.ieee.org/abstract/document/9169843 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2020_09169843.pdf Acesso restrito! | 3,96 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons