2016
Mendoza-Silva, Germán Martín; Torres-Sospedra, Joaquín; Huerta-Guijarro, Joaquín; Montoliu, Raul; Benítez, Fernando; Belmonte, Oscar
Situation Goodness Method for Weighted Centroid-Based Wi-Fi APs Localization Conference
Progress in Location-Based Services 2016, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-47289-8.
Abstract | Links | BibTeX | Tags: Indoor localization, Interpolation, LBS, Weighted centroid, Wi-Fi mapping
@conference{Mendoza-Silva2017,
title = {Situation Goodness Method for Weighted Centroid-Based Wi-Fi APs Localization},
author = {Germán Martín Mendoza-Silva and Joaquín Torres-Sospedra and Joaquín Huerta-Guijarro and Raul Montoliu and Fernando Benítez and Oscar Belmonte},
editor = {Gartner, Georg and Huang, Haosheng},
url = {http://dx.doi.org/10.1007/978-3-319-47289-8_2},
doi = {10.1007/978-3-319-47289-8_2},
isbn = {978-3-319-47289-8},
year = {2016},
date = {2016-10-13},
booktitle = {Progress in Location-Based Services 2016},
pages = {27--47},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Knowing the location of Wi-Fi antennas may be critical for indoor localization. However, in a real environment, their positions may be unknown since they can be managed by external entities. This paper introduces a new method for evaluating the suitability of using the weighted centroid method for the 2D localization of a Wi-Fi AP. The method is based on the idea that the weighted centroid method provides its best results when there are fingerprints taken around the AP. In order to find the probability of being in the presence of such situations, a natural neighbor interpolation method is used to find the regions with the highest signal strengths. A geometrical method is then used to characterize that probability based on the distribution of those regions in relation to the AP position estimation given by the weighted centroid method. The paper describes the testing location and the used Wi-Fi fingerprints database. That database is used to create new databases that recreate different sampling possibilities through a samples deletion strategy. The original database and the newly created ones are then used to evaluate the localization results of several AP localization methods and the new method proposed in this paper. The evaluation results have shown that the proposed method is able to provide a proper probability for the suitability of using the weighted centroid method for localizing a Wi-Fi AP.},
keywords = {Indoor localization, Interpolation, LBS, Weighted centroid, Wi-Fi mapping},
pubstate = {published},
tppubtype = {conference}
}
Knowing the location of Wi-Fi antennas may be critical for indoor localization. However, in a real environment, their positions may be unknown since they can be managed by external entities. This paper introduces a new method for evaluating the suitability of using the weighted centroid method for the 2D localization of a Wi-Fi AP. The method is based on the idea that the weighted centroid method provides its best results when there are fingerprints taken around the AP. In order to find the probability of being in the presence of such situations, a natural neighbor interpolation method is used to find the regions with the highest signal strengths. A geometrical method is then used to characterize that probability based on the distribution of those regions in relation to the AP position estimation given by the weighted centroid method. The paper describes the testing location and the used Wi-Fi fingerprints database. That database is used to create new databases that recreate different sampling possibilities through a samples deletion strategy. The original database and the newly created ones are then used to evaluate the localization results of several AP localization methods and the new method proposed in this paper. The evaluation results have shown that the proposed method is able to provide a proper probability for the suitability of using the weighted centroid method for localizing a Wi-Fi AP.