research-article

Indoor localization without infrastructure using the acoustic background spectrum

Authors:

Stephen P. Tarzia,

Peter A. Dinda,

Robert P. Dick,

Gokhan MemikAuthors Info & Claims

MobiSys '11: Proceedings of the 9th international conference on Mobile systems, applications, and services

Pages 155 - 168

https://doi.org/10.1145/1999995.2000011

Published: 28 June 2011 Publication History

Abstract

We introduce a new technique for determining a mobile phone's indoor location even when Wi-Fi infrastructure is unavailable or sparse. Our technique is based on a new ambient sound fingerprint called the Acoustic Background Spectrum (ABS). An ABS serves well as a room fingerprint because it is compact, easily computed, robust to transient sounds, and surprisingly distinctive. As with other fingerprint-based localization techniques, location is determined by measuring the current fingerprint and then choosing the "closest" fingerprint from a database. An experiment involving 33 rooms yielded 69% correct fingerprint matches meaning that, in the majority of observations, the fingerprint was closer to a previous visit's fingerprint than to any fingerprints from the other 32 rooms. An implementation of ABS-localization called Batphone is publicly available for Apple iPhones. We used Batphone to show the benefit of using ABS-localization together with a commercial Wi-Fi-based localization method. In this second experiment, adding ABS improved room-level localization accuracy from 30% (Wi-Fi only) to 69% (Wi-Fi and ABS). While Wi-Fi-based localization has difficulty distinguishing nearby rooms, Batphone performs just as well with nearby rooms; it can distinguish pairs of adjacent rooms with 92% accuracy.

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Index Terms

Indoor localization without infrastructure using the acoustic background spectrum
1. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

cover image ACM Conferences

MobiSys '11: Proceedings of the 9th international conference on Mobile systems, applications, and services

June 2011

430 pages

ISBN:9781450306430

DOI:10.1145/1999995

General Chair:
Ashok Agrawala
University of Maryland, USA
,
Program Chairs:
Mark D. Corner
UMass Amherst, USA
,
David Wetherall
University of Wash. & Intel Labs, USA

Copyright © 2011 ACM.

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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New York, NY, United States

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Published: 28 June 2011

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MobiSys'11

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SIGMOBILE

MobiSys'11: The 9th International Conference on Mobile Systems, Applications, and Services

June 28 - July 1, 2011

Maryland, Bethesda, USA

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Overall Acceptance Rate 274 of 1,679 submissions, 16%

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https://doi.org/10.3390/buildings14113347
Yonetani RBaba JFurukawa YKostakos VKay JHoang T(2024)RetailOpt: Opt-In, Easy-to-Deploy Trajectory Estimation from Smartphone Motion Data and Retail Facility InformationProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676623(125-132)Online publication date: 5-Oct-2024
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Xia ZRen YLi SOu JLiu HChen YFu SLi H(2024)Indoor Location Identification for Smart Speakers Leveraging 3-D Acoustic ImagesIEEE Transactions on Mobile Computing10.1109/TMC.2024.338016223:12(10720-10733)Online publication date: Dec-2024
https://doi.org/10.1109/TMC.2024.3380162
Luo WSong QYan ZTan RLin G(2024)Indoor Smartphone SLAM With Acoustic EchoesIEEE Transactions on Mobile Computing10.1109/TMC.2023.332339323:6(6634-6649)Online publication date: Jun-2024
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Ren YLi SChen CLiu HYu JChen YYang HLi H(2024)Robust Indoor Location Identification for Smartphones Using Echoes From Dominant ReflectorsIEEE Transactions on Mobile Computing10.1109/TMC.2023.3307695(1-17)Online publication date: 2024
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Xu SChen RGuo GHuang LLi ZQian LYe FChen L(2024)An Audio Fingerprinting Based Indoor Localization System: From Audio to ImageIEEE Sensors Journal10.1109/JSEN.2024.339404724:12(20154-20166)Online publication date: 15-Jun-2024
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