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Journal ArticleDOI

Location Fingerprinting With Bluetooth Low Energy Beacons

Ramsey Faragher, +1 more
- 06 May 2015 - 
- Vol. 33, Iss: 11, pp 2418-2428
TLDR
This work provides a detailed study of BLE fingerprinting using 19 beacons distributed around a ~600 m2 testbed to position a consumer device, and investigates the choice of key parameters in a BLE positioning system, including beacon density, transmit power, and transmit frequency.
Abstract
The complexity of indoor radio propagation has resulted in location-awareness being derived from empirical fingerprinting techniques, where positioning is performed via a previously-constructed radio map, usually of WiFi signals. The recent introduction of the Bluetooth Low Energy (BLE) radio protocol provides new opportunities for indoor location. It supports portable battery-powered beacons that can be easily distributed at low cost, giving it distinct advantages over WiFi. However, its differing use of the radio band brings new challenges too. In this work, we provide a detailed study of BLE fingerprinting using 19 beacons distributed around a $\sim\! 600\ \mbox{m}^2$ testbed to position a consumer device. We demonstrate the high susceptibility of BLE to fast fading, show how to mitigate this, and quantify the true power cost of continuous BLE scanning. We further investigate the choice of key parameters in a BLE positioning system, including beacon density, transmit power, and transmit frequency. We also provide quantitative comparison with WiFi fingerprinting. Our results show advantages to the use of BLE beacons for positioning. For one-shot (push-to-fix) positioning we achieve $30\ \mbox{m}^2$ ), compared to $100\ \mbox{m}^2$ ) and < 8.5 m for an established WiFi network in the same area.

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Citations
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Book ChapterDOI

Analysis of Distance and Similarity Metrics in Indoor Positioning Based on Bluetooth Low Energy

TL;DR: It is observed that there is an orientation that offers the best positioning performance with the combination of iBeacon protocol, channel 38 and Mahalanobis distance.
Proceedings Article

A Pre-processing Technique for BLE-based Indoor Localization

TL;DR: The proposed channel separation prep-rocessing technique can improve distance estimation based on the Received Signal Strength Indicator (RSSI) of the Bluetooth signal by achieving a Root Mean Squared Error of 1.194 and standard deviation of 0.713.
Proceedings ArticleDOI

Indoor Localization on Smartphone Using PDR and Sparse Deployed BLE Beacons in Large Open Area

TL;DR: Wang et al. as mentioned in this paper proposed a single beacon-based positioning method that is based on the RSS peak and user's walking direction, and adopted a robust RSS peak detection method to recognize the real RSS peak accurately.

LoRaWAN: Lost for Localization?

TL;DR: In this paper , the authors investigated the feasibility of LoRaWAN as a localization solution for work safety applications in the industrial scenario from different angles, based on two measurement campaigns conducted at the Brno University of Technology (BUT), Brno, Czech Republic, and the University Politechnica of Bucharest (UPB), Bucharest, Romania.
Proceedings ArticleDOI

A crowd-assisted architecture for securing BLE beacon-based IoT infrastructure

TL;DR: A crowd-assisted architecture for securing BLE beacons is proposed and it is found that the beacon ID can be changed by user's mobile phone within a 20 m range with probability of almost 100% under both stationary and mobile conditions.
References
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Journal ArticleDOI

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Proceedings ArticleDOI

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Journal ArticleDOI

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