Finding by Counting: A Probabilistic Packet Count Model for Indoor Localization in BLE Environments

被引:3
|
作者
De, Subham [1 ]
Chowdhary, Shreyans [1 ]
Shirke, Aniket [2 ]
Lo, Yat Long [1 ]
Kravets, Robin [1 ]
Sundaram, Hari [1 ]
机构
[1] Univ Illinois, Urbana, IL 61801 USA
[2] ITT Bombay, Mumbai, Maharashtra, India
关键词
Internet of Things; Indoor Localization; Bluetooth Low Energy; Probabilistic packet reception model;
D O I
10.1145/3131473.3131482
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We propose a probabilistic packet reception model for Bluetooth Low Energy (BLE) packets in indoor spaces and we validate the model by using it for indoor localization. We expect indoor localization to play an important role in indoor public spaces in the future. We model the probability of reception of a packet as a generalized quadratic function of distance, beacon power and advertising frequency. Then, we use a Bayesian formulation to determine the coefficients of the packet loss model using empirical observations from our testbed. We develop a new sequential Monte-Carlo algorithm that uses our packet count model. The algorithm is general enough to accommodate different spatial configurations. We have good indoor localization experiments: our approach has an average error of similar to 1.2m, 53% lower than the baseline range-free MonteCarlo localization algorithm.
引用
收藏
页码:67 / 74
页数:8
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