Abstract
The localization techniques became very popular and widely used in recent years. Popularization of mobile devices such as smartphones particularly increased the importance of wireless localization, including indoor localization. This paper deals with two issues. First, it examines the effectiveness of selected fingerprint based Wi-Fi indoor localization methods utilized in personal localization system with use of ordinary mobile phones in non-controlled active environment in the presence of dynamic interferences. Second, the new fingerprint based positioning algorithm wkNN-Bayes that combines k nearest neighbor approach with probabilistic algorithm based on Bayes theory using normal distribution to model signal strength distribution is presented.
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Fraś, M., Waśko, K., Wierzowiecki, T. (2016). Personal Wi-Fi Based Indoor Localization of Mobile Devices in Active Environment. In: Świątek, J., Borzemski, L., Grzech, A., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part III. Advances in Intelligent Systems and Computing, vol 431. Springer, Cham. https://doi.org/10.1007/978-3-319-28564-1_1
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DOI: https://doi.org/10.1007/978-3-319-28564-1_1
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