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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18 Apr 2020
TL;DR: The design of an indoor positioning system (IPS) using Bluetooth Low Energy scanners and beacons using K-Nearest Neighbour algorithm to predict the region where the beacon is possibly located and it is demonstate that the system is able to estimate the location region of the target beacon with good accuracy.
Abstract: In this paper we discuss the design of an indoor positioning system (IPS) using Bluetooth Low Energy (BLE) scanners and beacons. We deployed the prototype system in a laboratory where its dimension is measured at 990⨯770cm2, Range test has been carried out to study the relationship between distance and Received Signal Strength (RSSI) of the BLE devices. Using the highest RSSI values received from 3 of the scanners, we use K-Nearest Neighbour algorithm to predict the region where the beacon is possibly located. We further demonstate that our system is able to estimate the location region of the target beacon with good accuracy.
1 citations
05 Jun 2019-The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
TL;DR: A methodology that can be used to optimize such a deployment and thus, increase the performance of an indoor positioning system that a) is based on Received Signal Strength (RSS) fingerprinting and b) is orientated towards providing location or zone estimations instead of exact positioning.
Abstract: The performance of an indoor positioning system is highly related to the placement of the transmitting nodes that are used as references for the positioning estimations. In this paper, we propose a methodology that can be used to optimize such a deployment and thus, increase the performance of an indoor positioning system that a) is based on Received Signal Strength (RSS) fingerprinting and b) is orientated towards providing location or zone estimations instead of exact positioning. The optimization process involves 4 fundamental components. Firstly, the modelling of the obstructions in the indoor environment and also the zone modelling. Then, the definition of the performance metric that can be used to evaluate each different deployment scenario, in which case, our proposed metric considers the separation area and distances between the zones in the RSS vector space. The third component is the radio propagation model, required for simulating the RSSs from each node, where a model based on the ray tracing technique is selected. Finally, the last component is the selection of the optimization function that will control and drive the whole optimization process by selecting which deployment schemes to evaluate. For that, the utilization of a Genetic Algorithm is proposed. Although the evaluation of this methodology is outside the paper's scope, the key factors affecting the optimization performance the most, are expected to be a) the accuracy of the used indoor model and radio propagation model and b) the exact implementation of the optimization function.
1 citations
01 Jan 2021
TL;DR: In this paper, the authors presented an accurate and fast indoor positioning system using beacons and a server that manages pyramidal beacons in a mobile augmented reality environment, which consists of a beacon shaped for easy recognition in the image, a detector for recognizing such a pyramid beacon and extracting 6 degrees of freedom relative to the beacon, and a management server that manage the ID and location information of each pyramid beacon.
Abstract: This paper presents an accurate and fast indoor positioning system using beacons and a server that manages pyramidal beacons in a mobile augmented reality environment. The proposed system consists of a beacon shaped for easy recognition in the image, a detector for recognizing such a pyramidal beacon and extracting 6 degrees of freedom relative to the beacon, and a management server that manages the ID and location information of each pyramidal beacon. Because of the characteristics of the proposed method, the posture estimation including the position is also performed in the positioning. Therefore, it is possible to implement the augmented reality with a high degree of immersion and to manage a plurality of pyramidal beacons, thereby positioning them in a wide space like a large shopping mall. To manage a large number of beacons, an LED for identifying an ID exists in the center of the beacon, and the management server maps the beacon to the coordinates of the room. The positioning is performed by recognizing the pyramidal beacon through the model learned by deep learning in the mobile device, extracting 6 degrees of freedom relative to the pyramidal beacon recognized through the image-based technology, and receiving the indoor position through communication with the server. The proposed system can be applied to a user guidance service based on mobile augmented reality in a complex and wide indoor environment.
1 citations
TL;DR: RefRec+ as discussed by the authors estimates the 2D position of a point of interest (POI) by calculating the received signal strength of individual light sources using the floor image captured by the camera.
Abstract: This paper describes a novel visible light positioning (VLP) system called RefRec+ allowing to estimate the six degree-of-freedom (6DoF) of a smartphone. In most existing VLP systems, their front camera faces multiple light sources installed at different places on a ceiling to detect their direct signals. To overcome the problem of the limited field of views that causes failure to capture required numbers of light sources for positioning and that of the high computational complexity because of image processing to a large-sized pixel data, RefRec+ captures indirect lights from the light sources reflected via a floor. RefRec+ estimates the 2-D position of a point of interest (POI) by calculating the received signal strength of individual light sources using the floor image captured by the camera. Using 2-D positions of multiple POIs and the angle of arrival method, RefRec+ obtains the 6DoF of the smartphone. Several experiments to confirm the performance of RefRec+ were conducted. Experimental results in a room measuring 4.0 m × 4.0 m using nine POIs each of which consists of 32 × 32 pixels in a captured image showed that the absolute errors at the 90th percentile for the 3-D coordinates were 0.2073 m, 0.1713 m, and 0.002464 m along the X, Y, and Z axes, respectively, and for the pitch, roll, and yaw angles were 5.78, 5.69 and 3.96 degrees, respectively.
1 citations
HSBC1
TL;DR: It is believed that access to physical browsing information of shoppers in retail stores can not only provide crucial insights into shoppers’ needs and interests but also reveal the effectiveness of the store layout itself.
Abstract: The Internet of Things (IoT) has evolved from just being an experimental concept, and is now completely transforming the ways in which industries operate. Forbes calls the Internet of Things a giant network of connected things, with relationships between people and people, people and things, and things and things. We consider the problem of tracking physical browsing by users in indoor spaces such as retail stores[13]. Analogous to online browsing, where users choose to go to certain web pages, dwell on a subset of pages of interest to them, and click on links of interest while ignoring others, we can draw parallels in the physical setting, where a user might walk purposefully to a section of interest, dwell there for a while, gaze at specific items, and reach out for the ones that they wish to examine more closely. As our contribution, we design techniques to explore and track each of these elements of physical browsing using a combination of a smartphone shopping app which eases the customers' physical shopping experience and BLE beacons for [5]. We believe that access to physical browsing information of shoppers in retail stores can not only provide crucial insights into shoppers’ needs and interests but also reveal the effectiveness of the store layout itself.
1 citations
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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