scispace - formally typeset
Journal ArticleDOI

Location Fingerprinting With Bluetooth Low Energy Beacons

Ramsey Faragher, +1 more
- 06 May 2015 - 
- Vol. 33, Iss: 11, pp 2418-2428
Reads0
Chats0
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

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

BLE Beacons in the Smart City: Applications, Challenges, and Research Opportunities

TL;DR: The characteristics of BLE beacons, the applications that can benefit from them, and the challenges they pose while trying to identify research opportunities and future directions are discussed.
Journal ArticleDOI

FineLoc: A Fine-Grained Self-Calibrating Wireless Indoor Localization System

TL;DR: FineLoc is presented, a fine-grained self-calibrating localization system based on the freely-deployed Bluetooth low energy (BLE) nodes and crowdsourced data, which can profile more detailed layout information of the indoor space.
Proceedings ArticleDOI

LoRaIn: Making a Case for LoRa in Indoor Localization

TL;DR: Considering the coverage, stability and regularity of signals, accuracy of localization, responsiveness, power, and cost–the authors conclude that LoRa is a feasible choice for indoor localization solution, especially in wide and tall indoor environments like warehouses and multi-storied buildings.
Journal ArticleDOI

Random Forest Learning Based Indoor Localization as an IoT Service for Smart Buildings

TL;DR: In this article, a random forest based machine learning algorithm was proposed to improve the location accuracy in indoor localization as an IoT service for smart buildings and the obtained experimental results show 14% better success test prediction percentage in terms of overall deviation.
Proceedings ArticleDOI

InLoc: An end-to-end robust indoor localization and routing solution using mobile phones and BLE beacons

TL;DR: The paper proposes a novel approach for estimating the distance from BLE beacons using RSSI (Received Signal Strength Indication) measurement, and an efficient method for independent fusion of location information from phone IMU sensors and Bluetooth Low Energy beacons is demonstrated.
References
More filters
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.
Related Papers (5)