research-article

ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization

Authors:

Niranjini Rajagopal,

Bruno Sinopoli,

Anthony RoweAuthors Info & Claims

SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems

Pages 73 - 84

https://doi.org/10.1145/2809695.2809727

Published: 01 November 2015 Publication History

Abstract

The proliferation of Bluetooth Low-Energy (BLE) chipsets on mobile devices has lead to a wide variety of user-installable tags and beacons designed for location-aware applications. In this paper, we present the Acoustic Location Processing System (ALPS), a platform that augments BLE transmitters with ultrasound in a manner that improves ranging accuracy and can help users configure indoor localization systems with minimal effort. A user places three or more beacons in an environment and then walks through a calibration sequence with their mobile device where they touch key points in the environment like the floor and the corners of the room. This process automatically computes the room geometry as well as the precise beacon locations without needing auxiliary measurements. Once configured, the system can track a user's location referenced to a map.

The platform consists of time-synchronized ultrasonic transmitters that utilize the bandwidth just above the human hearing limit, where mobile devices are still sensitive and can detect ranging signals. To aid in the mapping process, the beacons perform inter-beacon ranging during setup. Each beacon includes a BLE radio that can identify and trigger the ultrasonic signals. By using differences in propagation characteristics between ultrasound and radio, the system can classify if beacons are within Line-Of-Sight (LOS) to the mobile phone. In cases where beacons are blocked, we show how the phone's inertial measurement sensors can be used to supplement localization data. We experimentally evaluate that our system can estimate three-dimensional beacon location with a Euclidean distance error of 16.1cm, and can generate maps with room measurements with a two-dimensional Euclidean distance error of 19.8cm. When tested in six different environments, we saw that the system can identify Non-Line-Of-Sight (NLOS) signals with over 80% accuracy and track a user's location to within less than 100cm.

References

[1]

Gimbal: http://www.gimbal.com/ (viewed 2/13/2015).

[2]

iBeacon: https://developer.apple.com/ibeacon/ (viewed 2/13/2015).

[3]

Dimitrios Lymberopoulos, Domenico Giustiniano, Vincent Lenders, Maurizio Rea, Andreas Marcaletti, et al. A realistic evaluation and comparison of indoor location technologies: Experiences and lessons learned. In Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, IPSN '14, 2015.

Digital Library

[4]

Patrick Lazik and Anthony Rowe. Indoor pseudo-ranging of mobile devices using ultrasonic chirps. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems, SenSys '12, pages 99--112, Toronto, Ontario, Canada, 2012. ACM.

Digital Library

[5]

Patrick Lazik, Niranjini Rajagopal, Bruno Sinopoli, and Anthony Rowe. Ultrasonic time synchronization and ranging on smartphones. In 21st IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS '14, 2014.

[6]

Nissanka B. Priyantha, Anit Chakraborty, and Hari Balakrishnan. The cricket location-support system. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (Mobicom '00), pages 32--43, New York, NY, USA, 2000. ACM.

Digital Library

[7]

B.W. Parkinson and S.W. Gilbert. Navstar: Global positioning system - ten years later. Proceedings of the IEEE, 71(10):1177 -- 1186, oct. 1983.

[8]

Gaetano Borriello, Alan Liu, Tony Offer, Christopher Palistrant, and Richard Sharp. Walrus: wireless acoustic location with room-level resolution using ultrasound. In Proceedings of the 3rd International Conference on Mobile Systems, Applications, and Services (MobiSys '05), pages 191--203, New York, NY, USA, 2005. ACM.

Digital Library

[9]

Kamin Whitehouse, Chris Karlof, Alec Woo, Fred Jiang, and David Culler. The effects of ranging noise on multihop localization: An empirical study. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, IPSN '05, Piscataway, NJ, USA, 2005. IEEE Press.

Digital Library

[10]

P. Bahl and V.N. Padmanabhan. Radar: an in-building rf-based user location and tracking system. In Proceedings of the 19th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '00), volume 2, pages 775 --784, 2000.

[11]

A. Ward, A. Jones, and A. Hopper. A new location technique for the active office. IEEE Personal Communications, 4(5):42 --47, oct 1997.

[12]

Konrad Lorincz and Matt Welsh. Motetrack: a robust, decentralized approach to rf-based location tracking. In Proceedings of the 1st International Conference on Location- and Context-Awareness (LoCA'05), pages 63--82, Berlin, Heidelberg, 2005. Springer-Verlag.

Digital Library

[13]

Stephen P. Tarzia, Peter A. Dinda, Robert P. Dick, and Gokhan Memik. Indoor localization without infrastructure using the acoustic background spectrum. In Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services (MobiSys '11), pages 155--168, New York, NY, USA, 2011. ACM.

Digital Library

[14]

Zhuoling Xiao, Hongkai Wen, Andrew Markham, and Niki Trigoni. Lightweight map matching for indoor localisation using conditional random fields. In Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, IPSN '14, pages 131--142, Piscataway, NJ, USA, 2014. IEEE Press.

Digital Library

[15]

Anshul Rai, Krishna Kant Chintalapudi, Venkata N. Padmanabhan, and Rijurekha Sen. Zee: Zero-effort crowdsourcing for indoor localization. In Proceedings of the 18th Annual International Conference on Mobile Computing and Networking, Mobicom '12, pages 293--304, New York, NY, USA, 2012. ACM.

Digital Library

[16]

Pengfei Zhou, Mo Li, and Guobin Shen. Use it free: Instantly knowing your phone attitude. In Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, MobiCom '14, pages 605--616, New York, NY, USA, 2014. ACM.

Digital Library

[17]

Isaac Amundson and Xenofon D. Koutsoukos. A survey on localization for mobile wireless sensor networks. In Proceedings of the 2nd International Conference on Mobile Entity Localization and Tracking in GPS-less Environments (MELT '09), pages 235--254, Berlin, Heidelberg, 2009. Springer-Verlag.

Digital Library

[18]

Kaveh Pahlavan, Xinrong Li, Mika Ylianttila, Ranvir Chana, and Matti Latva-aho. An overview of wireless indoor geolocation techniques and systems. In Proceedings of the IFIP-TC6/European Commission International Workshop on Mobile and Wireless Communication Networks (NETWORKING '00), pages 1--13, London, UK, UK, 2000. Springer-Verlag.

Digital Library

[19]

Zheng Sun, R. Farley, T. Kaleas, J. Ellis, and K. Chikkappa. Cortina: Collaborative context-aware indoor positioning employing rss and rtof techniques. In IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM '11 Workshops), pages 340 --343, march 2011.

[20]

Chunyi Peng, Guobin Shen, Zheng Han, Yongguang Zhang, Yanlin Li, and Kun Tan. A beepbeep ranging system on mobile phones. In Proceedings of the 5th International Conference on Embedded Networked Sensor Systems (SenSys '07), pages 397--398, New York, NY, USA, 2007. ACM.

Digital Library

[21]

Mike Hazas and Andy Ward. A novel broadband ultrasonic location system. In Proceedings of the 4th International Conference on Ubiquitous Computing (UbiComp '02), pages 264--280, London, UK, UK, 2002. Springer-Verlag.

Digital Library

[22]

Mike Hazas and Andy Ward. A high performance privacy-oriented location system. In Proceedings of the 1st IEEE International Conference on Pervasive Computing and Communications (PERCOM '03), pages 216--223, Washington, DC, USA, 2003. IEEE Computer Society.

Digital Library

[23]

Michael McCarthy, Paul Duff, Henk L. Muller, and Cliff Randell. Accessible ultrasonic positioning. IEEE Pervasive Computing, 5(4):86--93, October 2006.

Digital Library

[24]

Jie Yang, Simon Sidhom, Gayathri Chandrasekaran, Tam Vu, Hongbo Liu, Nicolae Cecan, Yingying Chen, Marco Gruteser, and Richard P. Martin. Detecting driver phone use leveraging car speakers. In Proceedings of the 17th Annual International Conference on Mobile Computing and Networking (MobiCom '11), pages 97--108, New York, NY, USA, 2011. ACM.

Digital Library

[25]

M.P. Wylie and J. Holtzman. The non-line of sight problem in mobile location estimation. In Universal Personal Communications, 1996. Record., 1996 5th IEEE International Conference on, volume 2, pages 827--831 vol.2, Sep 1996.

[26]

C. Tepedelenlioglu and G.B. Giannakis. On velocity estimation and correlation properties of narrow-band mobile communication channels. Vehicular Technology, IEEE Transactions on, 50(4):1039--1052, Jul 2001.

[27]

S. Venkatraman and J. Caffery. statistical approach to non-line-of-sight bs identification. In Wireless Personal Multimedia Communications, 2002. The 5th International Symposium on, volume 1, pages 296--300 vol.1, Oct 2002.

[28]

Zhuoling Xiao, Hongkai Wen, Andrew Markham, Niki Trigoni, Phil Blunsom, and Jeff Frolik. Non-line-of-sight identification and mitigation using received signal strength. Wireless Communications, IEEE Transactions on, 14(3):1689--1702, 2015.

[29]

David Moore, John Leonard, Daniela Rus, and Seth Teller. Robust distributed network localization with noisy range measurements. In Proceedings of the 2nd international conference on Embedded networked sensor systems, pages 50--61. ACM, 2004.

Digital Library

[30]

Joseph Djugash, Sanjiv Singh, George Kantor, and Wei Zhang. Range-only slam for robots operating cooperatively with sensor networks. In Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on, pages 2078--2084. IEEE, 2006.

[31]

L.L. Beranek. Acoustics. McGraw-Hill electrical and electronic engineering series. McGraw-Hill, 1954.

[32]

Hyewon Lee, Tae Hyun Kim, Jun Won Choi, and Sunghyun Choi. Chirp signal-based aerial acoustic communication for smart devices. In Computer Communications (INFOCOM), 2015 IEEE Conference on, pages 2407--2415, April 2015.

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Index Terms

ALPS: A Bluetooth and Ultrasound Platform for Mapping and Localization

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Published In

cover image ACM Conferences

SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems

November 2015

526 pages

ISBN:9781450336314

DOI:10.1145/2809695

General Chair:
Junehwa Song
KAIST, South Korea
,
Program Chairs:
Tarek Abdelzaher
University of Illinois at Urbana-Champaign, USA
,
Cecilia Mascolo
University of Cambridge, UK

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 November 2015

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SenSys '15: The 13th ACM Conference on Embedded Network Sensor Systems

November 1 - 4, 2015

Seoul, South Korea

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SenSys '15 Paper Acceptance Rate 27 of 132 submissions, 20%;

Overall Acceptance Rate 198 of 990 submissions, 20%

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https://doi.org/10.3390/s25041151
Lin YMatson NSundaresan K(2024)Bringing Collaborative Positioning to Native 5G Systems for Enhanced 2D & 3D Location ServicesProceedings of the ACM on Networking10.1145/36963802:CoNEXT4(1-21)Online publication date: 25-Nov-2024
https://dl.acm.org/doi/10.1145/3696380
Tian YWang YWang YTong XLiu XQu W(2024)Device-Free Human Tracking and Gait Recognition Based on the Smart SpeakerIEEE Transactions on Mobile Computing10.1109/TMC.2024.337964723:11(10610-10627)Online publication date: Nov-2024
https://doi.org/10.1109/TMC.2024.3379647
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Guo GChen RYan KLi ZQian LXu SNiu XChen L(2023)Large-Scale Indoor Localization Solution for Pervasive Smartphones Using Corrected Acoustic Signals and Data-Driven PDRIEEE Internet of Things Journal10.1109/JIOT.2023.326355110:17(15338-15349)Online publication date: 1-Sep-2023
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