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
More filters
TL;DR: This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice.
Abstract: Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice.
119 citations
Cites background from "Location Fingerprinting With Blueto..."
...In [112], the authors show that the BLE technology is strongly affected by the fast fading and interference, resulting in a low accuracy when detecting the user’s device....
[...]
TL;DR: A comprehensive survey of ML enabled localization techniques using most common wireless technologies for accurate indoor positioning and how the ML algorithms can be effectively used for fusing different technologies and algorithms to achieve a comprehensive IPS is provided.
Abstract: Widespread proliferation of wireless coverage has enabled culmination of number of advanced location-based services (LBS). Continuous tracking of accurate physical location is the foundation of these services, which is a challenging task especially indoors. Multitude of techniques and algorithms have been proposed for indoor positioning systems (IPS’s). However, accuracy, reliability, scalability and, adaptability to the environment still remain as challenges for widespread deployment. Especially, unpredictable radio propagation characteristics in vastly varying indoor environments plus access technology limitations contribute to these challenges. Machine learning (ML) approaches have been widely attempted recently to overcome these challenges with reasonable success. In this paper, we aim to provide a comprehensive survey of ML enabled localization techniques using most common wireless technologies. First, we provide a brief background on indoor localization techniques. Afterwards, we discuss various ML techniques (supervised and unsupervised) that could alleviate different challenges in indoor localization including Non-line-of-sight (NLOS) issue, device heterogeneity and environmental variations with reasonable complexity. The trade-offs among multitude of issues are discussed using numerous published results. We also discuss how the ML algorithms can be effectively used for fusing different technologies and algorithms to achieve a comprehensive IPS. In essence, this survey will serve as a reference material to acquire a detailed knowledge on recent development of machine learning for accurate indoor positioning.
119 citations
Cites background or methods from "Location Fingerprinting With Blueto..."
...To identify Wi-Fi APs from ZigBee interfaces they developed RSSI Quantification and RSSI Normalization....
[...]
...The authors in [78], compared the performance ofWi-Fi, BLE and ZigBee with simple RSSI-based trilateration method and found the achieved accuracy of Wi-Fi, BLE and ZigBee are 48.6 cm, 84.4 cm and 91.1 cm respectively....
[...]
...ML based solutions for fusion based localization. system where ZigBee interfaces are used to collect Wi-Fi signals....
[...]
...Bluetooth has been considered as a competitor to Wi-Fi due to the wide adaptability of Bluetooth Low Energy (BLE) by most smart phones [45]....
[...]
...[70] V. Bianchi, P. Ciampolini, and I. De Munari, ‘‘RSSI-based indoor localization and identification for ZigBee wireless sensor networks in smart homes,’’ IEEE Trans....
[...]
TL;DR: This survey gives a comprehensive review of state-of-the-art indoor localization methods and localization improvement methods using maps, spatial models, and landmarks.
Abstract: Indoor localization is essential for healthcare, security, augmented reality gaming, and many other location-based services. There is currently a wealth of relevant literature on indoor localization. This article focuses on recent advances in indoor localization methods that use spatial context to improve the location estimation. Spatial context in the form of maps and spatial models have been used to improve the localization by constraining location estimates in the navigable parts of indoor environments. Landmarks such as doors and corners, which are also one form of spatial context, have proved useful in assisting indoor localization by correcting the localization error. This survey gives a comprehensive review of state-of-the-art indoor localization methods and localization improvement methods using maps, spatial models, and landmarks.
117 citations
Cites background from "Location Fingerprinting With Blueto..."
...The new generation of Bluetooth low-energy technology, which consumes much less power than WiFi technology, is promising to be widely used for localization and navigation [37, 197]....
[...]
TL;DR: In this paper, the authors present a survey-style introduction to HLWNets, starting with a framework of system design in the aspects of network architectures, cell deployments, multiple access and modulation schemes, illumination requirements and backhaul.
Abstract: In order to tackle the rapidly growing number of mobile devices and their expanding demands for Internet services, network convergence is envisaged to integrate different technology domains. For indoor wireless communications, one promising approach is to coordinate light fidelity (LiFi) and wireless fidelity (WiFi), namely hybrid LiFi and WiFi networks (HLWNets). This hybrid network combines the high-speed data transmission of LiFi and the ubiquitous coverage of WiFi. In this article, we present a survey-style introduction to HLWNets, starting with a framework of system design in the aspects of network architectures, cell deployments, multiple access and modulation schemes, illumination requirements and backhaul. Key performance metrics and recent achievements are then reviewed to demonstrate the superiority of HLWNets against stand-alone networks. Further, the unique challenges facing HLWNets are elaborated on key research topics including user behavior modeling, interference management, handover and load balancing. Moreover, the potential of HLWNets in the application areas is presented, exemplified by indoor positioning and physical layer security. Finally, the challenges and future research directions are discussed.
116 citations
01 Aug 2015
TL;DR: This paper presents a range-based indoor localization system that exploits the Received Signal Strength (RSS) of Bluetooth Low Energy (BLE) beacon packets broadcast by anchor nodes and received by a BLE-enabled device.
Abstract: Localization of people and devices is one of the main building blocks of context aware systems since the user position represents the core information for detecting user's activities, devices activations, proximity to points of interest, etc. While for outdoor scenarios Global Positioning System (GPS) constitutes a reliable and easily available technology, for indoor scenarios GPS is largely unavailable. In this paper we present a range-based indoor localization system that exploits the Received Signal Strength (RSS) of Bluetooth Low Energy (BLE) beacon packets broadcast by anchor nodes and received by a BLE-enabled device. The method used to infer the user's position is based on stigmergy. We exploit the stigmergic marking process to create an on-line probability map identifying the user's position in the indoor environment.
113 citations
Cites background from "Location Fingerprinting With Blueto..."
...Experimental results in [10] have shown that BLE beacons present up to 30dB drops in the signal strength received by a mobile node moving towards them across just 10cm....
[...]
...To date, the only study based on BLE devices is the one proposed in [10], where authors analyze the application of fingerprinting techniques on BLE RSS values....
[...]
References
More filters
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]....
[...]
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....
[...]
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]....
[...]
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]....
[...]