Location Fingerprinting With Bluetooth Low Energy Beacons
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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01 Jan 2016
TL;DR: The co-phased combining scheme is found to perform better at low to intermediate pilot SNRs, in addition to being analytically tractable and having lower computational complexity, compared to the LMMSE-based scheme.
Abstract: This thesis proposes and analyzes data fusion algorithms that operate on the physical layer of a wireless sensor network, in the context of three applications of cognitive radios: 1. Cooperative spectrum sensing via binary consensus; 2. Multiple transmitter localization and communication footprint identification; 3.Target self-localization using beacon nodes.
For the first application, a co-phasing based data combining scheme is studied under imperfect channel knowledge. The evolution of network consensus state is modeled as a Markov chain, and the average transition probability matrix is derived. Using this, the average hitting time and average consensus duration are obtained, which are used to determine and optimize the performance of the consensus procedure.
Second, using the fact that a typical communication footprint map admits a sparse representation, two novel compressed sensing based schemes are proposed to construct the map using 1-bit decisions from sensors deployed in a geographical area. The number of transmitters is determined using the K-means algorithm and a circular fitting technique, and a design procedure is proposed to determine the power thresholds for signal detection at sensors.
Third, an algorithm is proposed for self-localization of a target node using power measurements from beacon nodes transmitting from known locations. The geographical area is overlaid with a virtual grid, and the problem is treated as one of testing overlapping subsets of grid cells for the presence of the target node. The column matching algorithm from group testing literature is considered for devising the target localization algorithm. The average probability of localizing the target within a grid cell is derived using the tools from Poisson point processes and order statistics. This quantity is used to determine the minimum required node density to localize the target within a grid cell with high probability.
The performance of all the proposed algorithms is illustrated through Monte Carlo simulations.
1 citations
Cites background from "Location Fingerprinting With Blueto..."
...In [104], the authors conduct an experimental study of fine-grained fingerprinting based localization using BLE devices as beacon nodes....
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01 Dec 2018
TL;DR: A real system is implemented and deployed in Guangzhou South Railway Station to enable a large scale indoor positioning service and it is found that the headings provided by HTML5 are not always correct, the orientation error scale has a strong correlation with the temperature of phone, and the residual error is accumulated along with the time.
Abstract: In the new era of wireless communication, there has been an increased interest in indoor positioning systems that propelled researchers to come up with various solutions. Fusing the fuzzy locations from Bluetooth (BT) beacons with the ones from pedestrian dead reckoning (PDR) comes out a promising solution to provide meter-level positioning without additional infrastructure. Despite the remarkable efforts the community put to build the system, it lacks the performance examination of large-scale deployments. In this report, we implement and deploy a real system in Guangzhou South Railway Station to enable a large scale indoor positioning service. The framework used Bluetooth beacons and pedestrian dead reckoning to calculate the estimated position of the user then refine the accuracy through a fuzzy fusion algorithm. We distribute up to 2849 beacons in the indoor space of 81654 square meters. When applied to the real ceiling with a height of 8m and above, our approach is still able to reliably achieve a high accuracy of 5 meters. Also in buildings whose outer walls are nonstructural but large glass curtain wall that wraps around the roof of the facility, the GPS signal could serve as useful complement under careful utilization; last but not least significant, in practice we incorporate our indoor positioning services into WeChat HyperText Markup Language (HTML) platform, we discover that the headings provided by HTML5 are not always correct, the orientation error scale has a strong correlation with the temperature of phone, the residual error is accumulated along with the time to make matters worse.
1 citations
Cites background from "Location Fingerprinting With Blueto..."
...What’s more, the access to Wi-Fi signal strength is not always with ease, it is widely known that this access is prohibited on some software like WeChat, or even Apple’s mobile operating system iOS [4], therefore, the inconvenience exerted by incompatibility of Wi-Fi positioning Fig....
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...The last decade has seen the development of indoor localization research [2][3][4][5][6][7][8][9][10], DWELT [10] validated the possibility of positioning in corridors, however he failed to illustrate how to extend an oversimplified 1-dimension scenario to real world....
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...In technical aspects, there exist a few commercial projects like shopping mall or hospital [11], but basically they rely on Wi-Fi as their main data source, the drawback of which is obvious: comparing to Bluetooth beacon, Wi-Fi installment must follow a strict deployment rule and always demand stable electricity supply, on the other hand, commercial area with WiFi-covered beforehand will be even more difficult to optimize as the existed irregularly distributed nodes may serve as noise disturbance[4]....
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01 Oct 2017
TL;DR: Simulation results indicate that the proposed algorithm improves the detection accuracy as compared to the conventional compressive sensing based algorithm and achieves substantial improvement in comparison with Mahalanobis and Euclidean-based similarity computation.
Abstract: Considering an incomplete signals acquisition due to a sparse beacon deployment, this paper proposes a generalized similarity filter to improve the performance of proximity detection and thus guarantee the quality of proximity-based service (PBS). In particular, this paper leverages Bluetooth Low Energy (BLE) Beacons to realize a PBS system which comprises a number of Proximities of Interest (PoIs). We define a PoI as an object or area which is associated with a beacon such that each PoI can announce their presence implicitly through the beacon's signal. However, under a sparse beacon network condition in which some beacons associated with some PoIs are malfunction or their batteries die before the scheduled maintenance, a receiver (e.g., smartphone) might fail to return the target PoI correctly. In view of the quality degradation in consequence to the sparse condition, we refine the performance of classical compressive sensing based algorithm with a generalized similarity filter. The effects of different similarity measures on proximity detection performance are also investigated. Simulation results indicate that the proposed algorithm improves the detection accuracy as compared to the conventional compressive sensing based algorithm. Specifically, Chordal-based similarity filter achieves substantial improvement in comparison with Mahalanobis and Euclidean-based similarity computation.
1 citations
Cites background from "Location Fingerprinting With Blueto..."
...Recently, the increasing demand of context awareness services require, in particular, the developement of indoor localization techniques [1][2][3]....
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...Indoor location-based services (LBSs) vary significantly from outdoor positioning systems, which rely on users to deliver their location information functionality via mobile applications [2][3]....
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TL;DR: In this article , a mobile crowdsourced guiding and finding (MCGF) framework using smartphones to guide indoor people and find missing targets through Internet-of-Things (IoT) localization is proposed.
Abstract: In this article, we propose a mobile crowdsourced guiding and finding (MCGF) framework using smartphones to guide indoor people and find missing targets through Internet-of-Things (IoT) localization. The MCGF framework can cooperatively find lost/stolen targets equipped with mobile iBeacon nodes through participatory sensing networks formed by mobile users using smartphones in places with static iBeacon nodes. To precisely localize the missing target, fundamental target localization cases in distinct crowdsourced environments are formally classified and efficiently addressed to reduce the positioning errors with different numbers of smartphones detecting the missing target and different numbers of fixed iBeacon nodes nearby these target-detecting smartphones. According to our review of relevant research, this is the first solution that can provide the crowdsourced guiding path to a missing target with high localization accuracy for all densities of participating smartphones and iBeacon nodes. In particular, an Android-based prototype with static and mobile iBeacon nodes is implemented to verify the feasibility and superiority of our framework. Experimental results show that MCGF outperforms the existing methods and can significantly reduce the localization errors of mobile users and missing targets.
1 citations
01 Jan 2019
TL;DR: This dissertation aims to provide a history of web exceptionalism from 1989 to 2002, a period chosen in order to explore its roots as well as specific cases up to and including the year in which descriptions of “Web 2.0” began to circulate.
Abstract: ............................................................................................................................. i Zusammenfassung ............................................................................................................. iii Acknowledgment ................................................................................................................v
1 citations
Cites background from "Location Fingerprinting With Blueto..."
...The influence of small-scale fading on the RSS values has been investigated in the literature [56], [57] but its influence on Wi-Fi fingerprinting has not been investigated yet....
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...In [57], the authors investigate the susceptibility to the fading effect of the Bluetooth signal....
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...The influence of small-scale fading on the RSS values has been investigated in the literature [56], [57]....
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References
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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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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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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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