Improving the Precision of Wireless Localization Algorithms: ML Techniques for Indoor Positioning

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU136956" target="_blank" >RIV/00216305:26220/20:PU136956 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TSP49548.2020.9163551" target="_blank" >http://dx.doi.org/10.1109/TSP49548.2020.9163551</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP49548.2020.9163551" target="_blank" >10.1109/TSP49548.2020.9163551</a>

Result language
angličtina
Original language name
Improving the Precision of Wireless Localization Algorithms: ML Techniques for Indoor Positioning
Original language description
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.
Czech name
—
Czech description
—

Project
<a href="/en/project/FV40371" target="_blank" >FV40371: New system for indoor 2D and 3D real time positioning for automation, visualization and control of work process using MEMS sensors and PDoA/AoA hybrid method</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
43nd International Conference on Telecommunications and Signal Processing (TSP 2020).
ISBN
978-1-7281-6376-5
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
1-6
Publisher name
IEEE
Place of publication
Neuveden
Event location
Milan, Italy
Event date
Jul 7, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000577106400126

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