Journal ArticleDOI
Location Fingerprinting With Bluetooth Low Energy Beacons
Ramsey Faragher,Robert Harle +1 more
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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.read more
Citations
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Proceedings ArticleDOI
Unsupervised indoor localization based on Smartphone Sensors, iBeacon and Wi-Fi
Yi Zhang,Jing Chen,Wei Xue +2 more
TL;DR: The experimental results show that the UILoc can provide accurate positioning and the average localization error is about 1.1 meters in the steady state and the maximum error is 2.77 meters.
Proceedings ArticleDOI
Experience: pushing indoor localization from laboratory to the wild
Jiazhi Ni,Fusang Zhang,Jie Xiong,Qiang Huang,Zhaoxin Chang,Junqi Ma,Binbin Xie,Pengsen Wang,Guangyu Bian,Xin Li,Changpin Li +10 more
TL;DR: In this article , the authors share their 5-year experience on the design, development and evaluation of a large-scale WiFi indoor localization system and address practical challenges encountered to bridge the gap between indoor localization research in the laboratory and system deployment in the wild.
Proceedings ArticleDOI
Neural Network Based Radio Fingerprint Similarity Measure
TL;DR: A new deep learning inspired model to predict locational distance/similarity between two points based on their RSSI measurement is presented, which combines the best features from all three reference models and generates the best locationaldistance estimation.
Book ChapterDOI
DE-auth of the Blue! Transparent De-authentication Using Bluetooth Low Energy Beacon
TL;DR: The so-called “lunchtime attack”, whereby a nearby attacker gains access to the casually departed user’s active log-in session, is a serious security risk that stems from lack of proper de-authentication.
Book ChapterDOI
Adapted WLAN Fingerprint Indoor Positioning System (IPS) Based on User Orientations
TL;DR: A new method is proposed to overcome the effect of user orientation on the accuracy of IPS by introducing an adaptation of the signal strength values based on user orientation and decreasing the required RM database memory with more additions of simple computations.
References
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Journal ArticleDOI
Survey of Wireless Indoor Positioning Techniques and Systems
TL;DR: Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
Proceedings ArticleDOI
The Horus WLAN location determination system
TL;DR: The Horus system identifies different causes for the wireless channel variations and addresses them and uses location-clustering techniques to reduce the computational requirements of the algorithm and the lightweight Horus algorithm helps in supporting a larger number of users by running the algorithm at the clients.
Journal ArticleDOI
A Survey of Indoor Inertial Positioning Systems for Pedestrians
TL;DR: It is concluded that PDR techniques alone can offer good short- to medium- term tracking under certain circumstances, but that regular absolute position fixes from partner systems will be needed to ensure long-term operation and to cope with unexpected behaviours.
Enhancements to the RADAR User Location and Tracking System
TL;DR: This paper analyzes shortcomings of the basic system, develops and evaluates solutions to address these shortcomings, and describes several new enhancements, including a novel access point-based environmental profiling scheme, and a Viterbi-like algorithm for continuous user tracking and disambiguation of candidate user locations.
Network Time Protocol Version 4: Protocol and Algorithms Specification
TL;DR: NTP version 4 (NTPv4), which is backwards compatible with NTP version 3 (N TPv3), described in RFC 1305, as well as previous versions of the protocol, are described.
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