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.
Citations
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TL;DR: An automatic daily report generation system that monitors the activities of nursing home residents and shows the most effective combination pattern among 156 patterns to accurately generate daily reports.
Abstract: As the world’s population of senior citizens continues to grow, the burden on the professionals who care for them (carers) is also increasing. In nursing homes, carers often write daily reports to improve the resident’s quality of life. However, since each carer needs to simultaneously care for multiple residents, they have difficulty thoroughly recording the activities of residents. In this paper, we address this problem by proposing an automatic daily report generation system that monitors the activities of nursing home residents. The proposed system estimates the multiple locations (areas) at which residents are situated with a BLE beacon, using a variety of methods to analyze the RSSI values of BLE signals, and recognizes the activity of each resident from the estimated area information. The information of the estimated activity of residents is stored in a server with timestamps, and the server automatically generates daily reports based on them. To show the effectiveness of the proposed system, we conducted an experiment for five days with four participants in cooperation with an actual nursing home. We determined the proposed system’s effectiveness with the following four evaluations: (1) comparison of performance of different machine-learning algorithms, (2) comparison of smoothing methods, (3) comparison of time windows, and (4) evaluation of generated daily reports. Our evaluations show the most effective combination pattern among 156 patterns to accurately generate daily reports. We conclude that the proposed system has high effectiveness, high usability, and high flexibility.
8 citations
Additional excerpts
...Location estimation techniques have been proposed based on several kinds of techniques, including Wi-Fi signals [26], BLE signals [3, 4, 27], magnetic fields [28], infrared [29], and ultrasounds [30]....
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01 Sep 2020
TL;DR: This scientific work is preparatory for the adoption of Machine Learning algorithms that will drive and optimise the configuration of WMN, directly deployed at the Edge, achieving advances for navigation services.
Abstract: Navigation Systems are challenging software solutions that can support users who move in unknown environments. In this context, Bluetooth Beacons can strongly benefit of Mesh configuration for the deployment of new efficient mobility services in Edge computing and Internet of Things (IoT) scenarios. In this paper, we investigate how to use the Wireless Mesh Network (WMN) concept for improving the indoor and outdoor Navigation Systems using low-cost Bluetooth devices. This scientific work is preparatory for the adoption of Machine Learning algorithms that will drive and optimise the configuration of WMN, directly deployed at the Edge, achieving advances for navigation services. Detailed analysis of Bluetooth Low Energy (BLE) signal propagation in both indoor and outdoor scenarios are reported, representing the starting point for forthcoming developments. Specifically, our analysis shows how BLE interference among beacons depends on the distance among beacons and transmitting power, and this open new opportunities in designing new optimization strategies to be executed at the Edge.
8 citations
Cites methods from "Location Fingerprinting With Blueto..."
...Faragher and Harle [5] implemented this method using 19 Bluetooth beacons over 600mq being able to achieve localization accuracy of less than 2....
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...Faragher and Harle [5] implemented this method using 19 Bluetooth beacons over 600mq being able to achieve localization accuracy of less than 2.6 m error in 95% of the case....
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TL;DR: This study proposes an indoor positioning system that is based on the deep Gaussian process regression (DGPR) model and it only needs to measure part of the reference points, thus reducing the time and cost required for data collection.
Abstract: With the widespread use of the Global Positioning System, indoor positioning technology has attracted increasing attention. Many systems with distinct deployment costs and positioning accuracies have been developed over the past decade for indoor positioning. The method that is based on received signal strength (RSS) is the most widely used. However, manually measuring RSS signal values to build a fingerprint database is costly and time-consuming, and it is impractical in a dynamic environment with a large positioning area. In this study, we propose an indoor positioning system that is based on the deep Gaussian process regression (DGPR) model. This model is a nonparametric model and it only needs to measure part of the reference points, thus reducing the time and cost required for data collection. The model converts the RSS values into four types of characterizing values as input data and then predicts the position coordinates using DGPR. Finally, after reinforcement learning, the position coordinates are optimized. The authors conducted several experiments on a simulated environment by MATLAB and physical environments at Tianjin University. The experiments examined different environments, different kernels, and positioning accuracy. The results showed that the proposed method could not only retain the positioning accuracy, but also save the computation time that is required for location estimation.
8 citations
Cites methods from "Location Fingerprinting With Blueto..."
...According to the broadcasting performance of Bluetooth beacon, we setup our transmitter up to 100 packages per second and 20 samples are collected at each location for the system evaluation [26,27]....
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Journal Article•
TL;DR: A novel method to allocate additional weights in order to compensate the intensity of signal generated in each device by using a double Gaussian filter is proposed to improve the accuracy of indoor location tracking using beacons.
Abstract: In this paper, we propose indoor location tracking method using RSSI(Received Signal Strength Indicator) value received from BLE(Bluetooth Low Energy) beacon. Due to the influence of various external environmental factors, it is very difficult to improve the accuracy in indoor location tracking. In order to solve this problem, we propose a novel method of reducing the noise generated in the external environment by using a double Gaussian filter. In addition, the value of the RSSI signal generated in the BLE beacon is different for each device. In this study, we propose a method to allocate additional weights in order to compensate the intensity of signal generated in each device. This makes it possible to improve the accuracy of indoor location tracking using beacons. The experiment results show that the proposed method effectively decrease the RSSI deviation and increase location accuracy. In order to verify the usefulness of this study, we compared the Kalman filter algorithm which is widely used in signal processing. We further performed additional experiments for application area for indoor location service and find that the proposed scheme is useful for BLE-based indoor location service.
8 citations
01 Dec 2015
TL;DR: A particle filter using the extended motion model in which all particles are constrained according to the map structure is presented and wireless local area network and Bluetooth Low Energy positioning tests show that the proposed algorithm outperforms comparison methods especially if the measurement rate is low.
Abstract: This article presents a probabilistic motion model that is based on an economical graph-based indoor map representation, such that the motion of the user is constrained according to the floor plan of a building. The floor plan is modeled as a combination of links and open space polygons that are connected by nodes. In the authors' earlier work the link transition probabilities in this graph are proportional to the total link lengths that are the total lengths of the subgraphs accessible by choosing the considered link option, and this article extends this model to include open space polygons as well. A particle filter using the extended motion model in which all particles are constrained according to the map structure is presented. Furthermore, wireless local area network and Bluetooth Low Energy positioning tests show that the proposed algorithm outperforms comparison methods especially if the measurement rate is low.
8 citations
Additional excerpts
...In this paper, a two-mode motion model is used to model the constrained motion of the user as in [3], [5] and [2]....
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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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