@inproceedings{bae29691566f4b569d3714fd55de39ee,
title = "Finding by counting: A probabilistic packet count model for indoor localization in BLE environments",
abstract = "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 ~1.2m, 53% lower than the baseline range-free Monte- Carlo localization algorithm.",
keywords = "Bluetooth Low Energy, Indoor Localization, Internet of Things, Probabilistic packet reception model",
author = "Subham De and Shreyans Chowdhary and Aniket Shirke and Lo, {Yat Long} and Robin Kravets and Hari Sundaram",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 11th Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization, WiNTECH 2017 ; Conference date: 20-10-2017",
year = "2017",
month = oct,
day = "20",
doi = "10.1145/3131473.3131482",
language = "English (US)",
series = "WiNTECH 2017 - Proceedings of the 11th Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization, co-located with MobiCom 2017",
publisher = "Association for Computing Machinery",
pages = "67--74",
booktitle = "WiNTECH 2017 - Proceedings of the 11th Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization, co-located with MobiCom 2017",
address = "United States",
}