Abstract
In this paper, we propose a Bluetooth Low Energy (BLE) iBeacon-based localization system, in which we combine two popular positioning methods: Pedestrian Dead Reckoning (PDR) and fingerprinting. As we build the system as an application running on an iPhone, we choose Kalman filter as the fusion algorithm to avoid complex computation. In fingerprinting, a multi-direction-database approach is applied. Finally, in order to reduce the cumulative error of PDR due to smartphone sensors, we propose an algorithm called “Distance-based Position Correction”. The aim of this algorithm is to occasionally correct the estimated position by using the iBeacon nearest to the user. In experiments, our system results in an average error of only 0.63 m.
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Acknowledgements
This work has been supported by Vietnam National University, Hanoi (VNU), under Project No. QG.19.25.
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Trinh, A.VT., Dinh, TM.T., Nguyen, QT., Sandrasegaran, K. (2020). Indoor Positioning Using BLE iBeacon, Smartphone Sensors, and Distance-Based Position Correction Algorithm. In: Solanki, V., Hoang, M., Lu, Z., Pattnaik, P. (eds) Intelligent Computing in Engineering. Advances in Intelligent Systems and Computing, vol 1125. Springer, Singapore. https://doi.org/10.1007/978-981-15-2780-7_105
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DOI: https://doi.org/10.1007/978-981-15-2780-7_105
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