Integration of BLE-Based Proximity Detection with Particle Filter for Day-Long Stability in Workplaces

Satoki Ogiso, Ikue Mori, Takahiro Miura, Satoshi Nakae, Takashi Okuma, Yasunori Haga, Shintaro Hatakeyama, Kengo Kimura, Atsushi Kimura, Takeshi Kurata

Abstract:	Abstract—In this paper, a particle filter that integrates proximity detection via Bluetooth Low Energy (BLE) is proposed. The proposed particle filter provides intermittent but reliable location coordinates. As a result, particles do not disappear from their original locations even over long measurement periods. The proposed method was evaluated in two real-world factory environments over 13 days with a total of 33 factory workers. A total of 901.5 and 1320.2 hours of data were measured in factory 1 and factory 2, respectively. From the measured data, we confirmed that the proposed method could measure typical flow lines for each worker role throughout the experimental period. We report on the measured data by comparing the results of the flow line measurement for the workers’ roles and the location estimation results for the received BLE signal obtained throughout the experimental period. Index Terms—indoor positioning, pedestrian dead reckoning, BLE RSSI, particle filter
Published in:	2023 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 24 - 27, 2023 Hyatt Regency Hotel Monterey, CA
Pages:	1060 - 1065
Cite this article:	Ogiso, Satoki, Mori, Ikue, Miura, Takahiro, Nakae, Satoshi, Okuma, Takashi, Haga, Yasunori, Hatakeyama, Shintaro, Kimura, Kengo, Kimura, Atsushi, Kurata, Takeshi, "Integration of BLE-Based Proximity Detection with Particle Filter for Day-Long Stability in Workplaces," 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, April 2023, pp. 1060-1065. https://doi.org/10.1109/PLANS53410.2023.10140037
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