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Journal ArticleDOI

Location Fingerprinting With Bluetooth Low Energy Beacons

06 May 2015-IEEE Journal on Selected Areas in Communications (IEEE)-Vol. 33, Iss: 11, pp 2418-2428
TL;DR: 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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Proceedings ArticleDOI
01 Jul 2017
TL;DR: In this article, the authors developed a prototypical application with which measurements are taken using different BLE hardware and showed that location tracking is only applicable to a limited extent using BLE technology and path loss model.
Abstract: Real-time location tracking systems (RTLS) for personnel and machinery in outdoor civil engineering environments quite often use commercially-available Global Navigation Satellite System (GNSS) technology. Although the GNSS is an important approach in outdoor positioning and logistics coordination, their signals are not able to penetrate buildings due to their signal strength. Despite some recent advances in research, reliable indoor navigation remains an unsolved problem. This work deals with a detailed study of the methods and approaches of indoor location tracking. The focus lies on systems based on Bluetooth Low Energy (BLE) technology that meet the specific requirements of construction site and facility management. The authors develop a prototypical application with which measurements are taken using different BLE hardware. The experiments show that location tracking is only applicable to a limited extent using BLE technology and path loss model. There were great differences in the behavior of different devices observed since the environment greatly influences the signal transmission. Proposed is an alternative, holistic system for location tracking using BLE. It uses a systematic classification of the work space by positioning the BLE beacons according to the a-priori known spatial building structure from a Building Information Model (BIM). By the relative observation of the received signal strengths of the individual beacons spread on a building floor, the calibration of the receivers is obsolete so that several different or alternative device types can be used together at the same time.

6 citations


Cites background from "Location Fingerprinting With Blueto..."

  • ...This way, interference and damping of individual signals no longer influence the localization and relatively high measuring accuracies and repeatability can be achieved [4]....

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Proceedings ArticleDOI
01 Oct 2018
TL;DR: This paper investigates three popular BLE beacon devices available on the market and compares them in terms of energy consumption and proximity accuracy for indoor localization services and develops two state-estimation filters for the Android mobile platform in order to improve the proximity accuracy when using smartphone devices.
Abstract: In the Internet of Things (IoT) era, with millions of connected devices to the internet, indoor location services regarding room discovery and resource identification/tracking are among the most popular applications for smart homes and smart buildings. Bluetooth Low Energy (BLE) beacons are a promising solution to improve the scalability and accuracy of indoor localization applications. They are low cost, configurable, small transmitters designed to attract attention to a specific location. In this paper, we investigate three popular BLE beacon devices available on the market and compare them in terms of energy consumption and proximity accuracy for indoor localization services. In addition, two state-estimation filters are developed for the Android mobile platform in order to improve the proximity accuracy when using smartphone devices. Specifically, a static Kalman filter and Gaussian filter are implemented.

6 citations


Cites methods from "Location Fingerprinting With Blueto..."

  • ...The fundamental operation of these beacons for localization purposes is based on RSSI techniques [10], [11], where the RSSI value is translated into a distance by using a best curve-fit signal propagation model....

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Journal ArticleDOI
TL;DR: This work reduces the dimensions of the positioning algorithm from 3-D to one-dimensional and proposes a fitness function based on the simple geometric relationship between light-emitting diodes’ projection circles in the horizontal plane that is practical and efficient, showing great application prospects in indoor positioning.
Abstract: Visible light positioning has a good application prospect because of its simultaneous lighting, convenience, and security. However, most existing visible light communication (VLC) positioning systems cannot achieve real three-dimensional (3-D) positioning but just the small range approximation or fail to provide satisfactory positioning precision and speed. We propose a 3-D indoor localization system based on VLC using improved bacterial colony chemotaxis algorithm. The positioning problem is transformed into a global optimization problem. We reduce the dimensions of the positioning algorithm from 3-D to one-dimensional and propose a fitness function based on the simple geometric relationship between light-emitting diodes’ projection circles in the horizontal plane. In addition, we improve the traditional bacterial colony chemotaxis algorithm by adopting self-adaptive reception scope to improve global convergence and introducing differential evolution operator to overcome the algorithm premature. Our simulation results show that the mean positioning error is 0.73 mm in an indoor space of 5 m × 5 m × 6 m and the positioning time for a single point is 21.8 ms. Also, the positioning results show the advantages of the proposed positioning algorithm with high precision and high speed. The proposed positioning algorithm is practical and efficient, showing great application prospects in indoor positioning.

6 citations

Journal ArticleDOI
TL;DR: An indoor, room-level tracking method is presented, which is characterized by an infrastructure that is cost-effective to build and maintain with no need to deal with calibration issues of the fingerprint map caused by hardware heterogeneity.
Abstract: Existing indoor positioning technologies aim at providing location information of extremely high accuracy, but are limited by the requirement for infrastructure with high installation and maintenance costs. Thus, for indoor human tracking applications, a suitable indoor positioning technique should be selected by taking into account practical considerations of adequate accuracy as well as cost-effectiveness. Based on this observation, an indoor, room-level tracking method is presented, which is characterized by an infrastructure that is cost-effective to build and maintain with no need to deal with calibration issues of the fingerprint map caused by hardware heterogeneity. A mobile device tracks variations in the radio signal strength from nearby Bluetooth beacons to determine the entry and exit of the user’s device from a given room or hallway. Therefore, by determining the sequence of users’ movements, their moving path can be recorded for indoor tracking or navigation. Experiments revealed that the proposed method attains an average hit rate, false alarm rate, and miss rate of 94.2%, 3.6%, and 5.8%, respectively.

6 citations

Journal ArticleDOI
TL;DR: In this paper , the authors proposed three real-time NLOS/LOS identification methods for smartphone-based indoor positioning systems using WiFi RSS and RTT distance measurement (RDM), based on an extensive analysis of RSS and RDM dispersion features, three machine learning algorithms were chosen and developed to separate the samples for NLOS andLOS conditions.
Abstract: The accuracy of smartphone-based positioning systems using WiFi usually suffers from ranging errors caused by non-line-of-sight (NLOS) conditions. Previous research usually exploits several distribution features from a long time series (hundreds of samples) of WiFi received signal strength (RSS) or WiFi round-trip time (RTT) to achieve a high identification accuracy. However, the long time series or large sample size attributes to high power and time consumption in data collection for both training and testing. This will also undoubtedly be detrimental to user experience as the waiting time for getting enough samples is quite long. Therefore, this paper proposes three new real-time NLOS/LOS identification methods for smartphone-based indoor positioning systems using WiFi RSS and RTT distance measurement (RDM). Based on our extensive analysis of RSS and RDM dispersion features, three machine learning algorithms were chosen and developed to separate the samples for NLOS/LOS conditions. Experiments show that our best method achieves a discrimination accuracy of over 96% with a sample size of 10. Considering the theoretically shortest WiFi ranging interval of 100ms of the RTT-enabled smartphones, our algorithm is able to provide the shortest latency of 1s to get the testing result among all of the state-of-art methods.

6 citations

References
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Journal ArticleDOI
01 Nov 2007
TL;DR: Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

4,123 citations


"Location Fingerprinting With Blueto..." refers background in this paper

  • ...Indoor positioning is a mature research field, with many proposed technologies and techniques—comprehensive overviews can be found in [2], [18], [19]....

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Proceedings ArticleDOI
06 Jun 2005
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.
Abstract: We present the design and implementation of the Horus WLAN location determination system. The design of the Horus system aims at satisfying two goals: high accuracy and low computational requirements. The Horus system identifies different causes for the wireless channel variations and addresses them to achieve its high accuracy. It uses location-clustering techniques to reduce the computational requirements of the algorithm. The lightweight Horus algorithm helps in supporting a larger number of users by running the algorithm at the clients.We discuss the different components of the Horus system and its implementation under two different operating systems and evaluate the performance of the Horus system on two testbeds. Our results show that the Horus system achieves its goal. It has an error of less than 0.6 meter on the average and its computational requirements are more than an order of magnitude better than other WLAN location determination systems. Moreover, the techniques developed in the context of the Horus system are general and can be applied to other WLAN location determination systems to enhance their accuracy. We also report lessons learned from experimenting with the Horus system and provide directions for future work.

1,631 citations


"Location Fingerprinting With Blueto..." refers background in this paper

  • ...Here the focus is on radio positioning, specifically using the empirical fingerprinting techniques [3], [15], [17], [22] that avoid the need to model the complex radio propagation environment indoors by patternmatching to a previously surveyed map of radio signal strengths....

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Journal ArticleDOI
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.
Abstract: With the continual miniaturisation of sensors and processing nodes, Pedestrian Dead Reckoning (PDR) systems are becoming feasible options for indoor tracking. These use inertial and other sensors, often combined with domain-specific knowledge about walking, to track user movements. There is currently a wealth of relevant literature spread across different research communities. In this survey, a taxonomy of modern PDRs is developed and used to contextualise the contributions from different areas. Techniques for step detection, characterisation, inertial navigation and step-and-heading-based dead-reckoning are reviewed and compared. Techniques that incorporate building maps through particle filters are analysed, along with hybrid systems that use absolute position fixes to correct dead-reckoning output. In addition, consideration is given to the possibility of using smartphones as PDR sensing devices. The survey concludes 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. It concludes by identifying a detailed list of challenges for PDR researchers.

749 citations


"Location Fingerprinting With Blueto..." refers background in this paper

  • ...fingerprints with other sources to form hybrid systems, many of which are based on the idea of Simultaneous Localization and Mapping (SLAM) [10], [16] being applied to pedestrian dead reckoning [13]....

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01 Feb 2000
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.
Abstract: We address the problem of locating users inside buildings using a radio-frequency (RF) wireless LAN. A previous paper presented the basic design and a limited evaluation of a user-location system we have developed. In this paper, we analyze shortcomings of the basic system, and develop and evaluate solutions to address these shortcomings. Additionally, we describe 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. Using extensive data collected from our deployment, we evaluate our system’s performance over multiple wireless LAN technologies and in different buildings on our campus. We also discuss significant practical issues that arise in implementing such a system. Our techniques are implemented purely in software and are easily deployable over a standard wireless LAN.

608 citations

01 Jun 2010
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.
Abstract: The Network Time Protocol (NTP) is widely used to synchronize computer clocks in the Internet. This document describes NTP version 4 (NTPv4), which is backwards compatible with NTP version 3 (NTPv3), described in RFC 1305, as well as previous versions of the protocol. NTPv4 includes a modified protocol header to accommodate the Internet Protocol version 6 address family. NTPv4 includes fundamental improvements in the mitigation and discipline algorithms that extend the potential accuracy to the tens of microseconds with modern workstations and fast LANs. It includes a dynamic server discovery scheme, so that in many cases, specific server configuration is not required. It corrects certain errors in the NTPv3 design and implementation and includes an optional extension mechanism. [STANDARDS-TRACK]

605 citations


"Location Fingerprinting With Blueto..." refers methods in this paper

  • ...Before each experiment, each clock was manually synchronized using a Network Time Protocol (NTP) server [20]....

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