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MAŠEK, P. SEDLÁČEK, P. OMETOV, A. MEKYSKA, J. MLÝNEK, P. HOŠEK, J. KOMAROV, M.
Originální název
Improving the Precision of Wireless Localization Algorithms: ML Techniques for Indoor Positioning
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Due to the tremendous increase in the number of wearable devices and proximity-based services, the need for improved indoor localization techniques becomes more significant. The evolution of the positioning from a hardware perspective is pacing its way along with various software-based approaches also powered by Machine Learning (ML). In this paper, we apply ML algorithms to the real-life collected signal parameters in an indoor localization system based on Ultra-Wideband (UWB) technology to make an analysis of the signal and classify it accordingly. The contribution aims to answer the question of whether an indoor positioning system could benefit from utilizing ML for signal parameter analysis in order to increase its location accuracy, reliability, and robustness across various environments. To this end, we compare different applications of ML approaches and detail the trade-off between computational speed and accuracy.
Klíčová slova
Indoor Positioning Systems; Ultra-Wideband; UWB; Machine Learning; Precision Improvement
Autoři
MAŠEK, P.; SEDLÁČEK, P.; OMETOV, A.; MEKYSKA, J.; MLÝNEK, P.; HOŠEK, J.; KOMAROV, M.
Vydáno
11. 8. 2020
Nakladatel
IEEE
ISBN
978-1-7281-6376-5
Kniha
43nd International Conference on Telecommunications and Signal Processing (TSP 2020).
Strany od
1
Strany do
6
Strany počet
BibTex
@inproceedings{BUT164722, author="Pavel {Mašek} and Petr {Sedláček} and Aleksandr {Ometov} and Jiří {Mekyska} and Petr {Mlýnek} and Jiří {Hošek} and Mikhail {Komarov}", title="Improving the Precision of Wireless Localization Algorithms: ML Techniques for Indoor Positioning", booktitle="43nd International Conference on Telecommunications and Signal Processing (TSP 2020).", year="2020", pages="1--6", publisher="IEEE", doi="10.1109/TSP49548.2020.9163551", isbn="978-1-7281-6376-5" }