Smartphone User Location Initialization in Multi-Floor Indoor Localization Using Magnentic Field Map and Deep Learning Model 


Vol. 49,  No. 12, pp. 1698-1701, Dec.  2024
10.7840/kics.2024.49.12.1698


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  Abstract

In this paper, we propose a 3D location initialization method that combines a magnetic field map and a deep learning model to detect the initial floor and 2D location of a smartphone user, addressing the challenges of multi-floor indoor localization. The proposed method meets the requirements of infrastructure-free multi-floor indoor localization, and experiments have validated its performance in estimating the user's 3D position.

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[IEEE Style]

J. Kim, S. Cho, Y. Shin, "Smartphone User Location Initialization in Multi-Floor Indoor Localization Using Magnentic Field Map and Deep Learning Model," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 12, pp. 1698-1701, 2024. DOI: 10.7840/kics.2024.49.12.1698.

[ACM Style]

Jin-Woo Kim, Sanghoon Cho, and Yoan Shin. 2024. Smartphone User Location Initialization in Multi-Floor Indoor Localization Using Magnentic Field Map and Deep Learning Model. The Journal of Korean Institute of Communications and Information Sciences, 49, 12, (2024), 1698-1701. DOI: 10.7840/kics.2024.49.12.1698.

[KICS Style]

Jin-Woo Kim, Sanghoon Cho, Yoan Shin, "Smartphone User Location Initialization in Multi-Floor Indoor Localization Using Magnentic Field Map and Deep Learning Model," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 12, pp. 1698-1701, 12. 2024. (https://doi.org/10.7840/kics.2024.49.12.1698)
Vol. 49, No. 12 Index