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Open AccessArticle

Collaborative Smartphone-Based User Positioning in a Multiple-User Context Using Wireless Technologies

1
Human Machine Interaction, University of Engineering and Technology, Vietnam National University, Hanoi 100000, Vietnam
2
MICA Institute (HUST-Grenoble INP), Hanoi University of Science and Technology, Hanoi 100000, Vietnam
3
University of Grenoble Alpes, CNRS, Inria, Grenoble INP, LIG, 38000 Grenoble, France
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Ta, V.-C.; Dao, T.-K.; Vaufreydaz, D.; Castelli, E. Smartphone-based user positioning in a multiple-user context with Wi-Fi and Bluetooth. In Proceedings of the IPIN 2018—9th International Conference on Indoor Positioning and Indoor Navigation, Nantes, France, 24–27 September 2018; pp. 1–13.
Sensors 2020, 20(2), 405; https://doi.org/10.3390/s20020405
Received: 6 December 2019 / Revised: 29 December 2019 / Accepted: 4 January 2020 / Published: 10 January 2020
For the localization of multiple users, Bluetooth data from the smartphone is able to complement Wi-Fi-based methods with additional information, by providing an approximation of the relative distances between users. In practice, both positions provided by Wi-Fi data and relative distance provided by Bluetooth data are subject to a certain degree of noise due to the uncertainty of radio propagation in complex indoor environments. In this study, we propose and evaluate two approaches, namely Non-temporal and Temporal ones, of collaborative positioning to combine these two cohabiting technologies to improve the tracking performance. In the Non-temporal approach, our model establishes an error observation function in a specific interval of the Bluetooth and Wi-Fi output. It is then able to reduce the positioning error by looking for ways to minimize the error function. The Temporal approach employs an extended error model that takes into account the time component between users’ movements. For performance evaluation, several multi-user scenarios in an indoor environment are set up. Results show that for certain scenarios, the proposed approaches attain over 40% of improvement in terms of average accuracy. View Full-Text
Keywords: indoor localization; indoor navigation; multi-sensor fusion; multiple-user positioning indoor localization; indoor navigation; multi-sensor fusion; multiple-user positioning
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MDPI and ACS Style

Ta, V.-C.; Dao, T.-K.; Vaufreydaz, D.; Castelli, E. Collaborative Smartphone-Based User Positioning in a Multiple-User Context Using Wireless Technologies. Sensors 2020, 20, 405.

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