research-article

No need to war-drive: unsupervised indoor localization

Authors:

Ahmed Elgohary,

Moustafa Farid,

Moustafa Youssef,

Romit Roy ChoudhuryAuthors Info & Claims

MobiSys '12: Proceedings of the 10th international conference on Mobile systems, applications, and services

Pages 197 - 210

https://doi.org/10.1145/2307636.2307655

Published: 25 June 2012 Publication History

Abstract

We propose UnLoc, an unsupervised indoor localization scheme that bypasses the need for war-driving. Our key observation is that certain locations in an indoor environment present identifiable signatures on one or more sensing dimensions. An elevator, for instance, imposes a distinct pattern on a smartphone's accelerometer; a corridor-corner may overhear a unique set of WiFi access points; a specific spot may experience an unusual magnetic fluctuation. We hypothesize that these kind of signatures naturally exist in the environment, and can be envisioned as internal landmarks of a building. Mobile devices that "sense" these landmarks can recalibrate their locations, while dead-reckoning schemes can track them between landmarks. Results from 3 different indoor settings, including a shopping mall, demonstrate median location errors of 1:69m. War-driving is not necessary, neither are floorplans the system simultaneously computes the locations of users and landmarks, in a manner that they converge reasonably quickly. We believe this is an unconventional approach to indoor localization, holding promise for real-world deployment.

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Cited By

Kim DSuh Y(2024)Automatic Fingerprint Data Labeling Using WiFi Signal and Smartphone Camera for Indoor PositioningWireless Communications and Mobile Computing10.1155/2024/86632462024:1Online publication date: 10-Jun-2024
https://doi.org/10.1155/2024/8663246
Sheshadri SHara K(2024)Conversational LocalizationProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314047:4(1-32)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631404
Li DXu JYang ZTang C(2024)Train Once, Locate Anytime for Anyone: Adversarial Learning-based Wireless LocalizationACM Transactions on Sensor Networks10.1145/361409520:2(1-21)Online publication date: 10-Jan-2024
https://dl.acm.org/doi/10.1145/3614095
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No need to war-drive: unsupervised indoor localization

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Published In

cover image ACM Conferences

MobiSys '12: Proceedings of the 10th international conference on Mobile systems, applications, and services

June 2012

548 pages

ISBN:9781450313018

DOI:10.1145/2307636

General Chair:
Nigel Davies
Lancaster University, UK
,
Program Chairs:
Srinivasan Seshan
Carnegie Mellon University, USA
,
Lin Zhong
Rice University, USA

Copyright © 2012 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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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 25 June 2012

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MobiSys'12

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MobiSys'12: The 10th International Conference on Mobile Systems, Applications, and Services

June 25 - 29, 2012

Lake District, Low Wood Bay, UK

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

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Cited By

Kim DSuh Y(2024)Automatic Fingerprint Data Labeling Using WiFi Signal and Smartphone Camera for Indoor PositioningWireless Communications and Mobile Computing10.1155/2024/86632462024:1Online publication date: 10-Jun-2024
https://doi.org/10.1155/2024/8663246
Sheshadri SHara K(2024)Conversational LocalizationProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314047:4(1-32)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631404
Li DXu JYang ZTang C(2024)Train Once, Locate Anytime for Anyone: Adversarial Learning-based Wireless LocalizationACM Transactions on Sensor Networks10.1145/361409520:2(1-21)Online publication date: 10-Jan-2024
https://dl.acm.org/doi/10.1145/3614095
Yang HXia ZShin JHua JMao YZhong S(2024)A Comprehensive Study of Trajectory Forgery and Detection in Location-Based ServicesIEEE Transactions on Mobile Computing10.1109/TMC.2023.327341123:4(3228-3242)Online publication date: Apr-2024
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Wang YWong AChan SMow W(2024)Leto: Crowdsourced Radio Map Construction With Learned Topology and a Few LandmarksIEEE Transactions on Mobile Computing10.1109/TMC.2023.326619823:4(2795-2812)Online publication date: Apr-2024
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Wang MLi LLiu JChen R(2024)Neural Network Aided Factor Graph Optimization for Collaborative Pedestrian NavigationIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.330996325:1(303-314)Online publication date: Jan-2024
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Wang CSong YZhang SChen SLi MChen P(2024)Hierarchical Trajectory Matching via Multilayered Map ModelIEEE Sensors Journal10.1109/JSEN.2024.339622724:12(20231-20239)Online publication date: 15-Jun-2024
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Ren XZhu SLiu FLi HLi HXiao XGao RZhang Z(2024)Help You Locate the Car: A Smartphone-Based Car-Finding System in Underground Parking LotIEEE Sensors Journal10.1109/JSEN.2024.334938524:5(7107-7118)Online publication date: 1-Mar-2024
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Morais JAlkhateeb A(2024)Localization in Digital Twin MIMO Networks: A Case for Massive Fingerprinting2024 IEEE International Conference on Communications Workshops (ICC Workshops)10.1109/ICCWorkshops59551.2024.10615652(276-281)Online publication date: 9-Jun-2024
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Liu YYang ZLiu YYang Z(2024)Automatic Fingerprint Database UpdateLocation, Localization, and Localizability10.1007/978-981-97-3176-3_9(163-185)Online publication date: 12-Jul-2024
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