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SmartLoc: push the limit of the inertial sensor based metropolitan localization using smartphone

Authors:

Yue Tao,

Lan YaoAuthors Info & Claims

MobiCom '13: Proceedings of the 19th annual international conference on Mobile computing & networking

Pages 195 - 198

https://doi.org/10.1145/2500423.2504574

Published: 30 September 2013 Publication History

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Abstract

We present SmartLoc, a localization system to estimate the location and the traveling distance by leveraging the lower-power inertial sensors embedded in smartphones as a supplementary to GPS. To minimize the negative impact of sensor noises, SmartLoc exploits the intermittent strong GPS signals and uses the linear regression to build a prediction model which is based on the trace estimated from inertial sensors and the one computed from the GPS. Furthermore, we utilize landmarks (e.g., bridge, traffic lights) detected automatically and special driving patterns (e.g., turning, uphill, and downhill) from inertial sensory data to improve the localization accuracy when the GPS signal is weak. Our evaluations of SmartLoc in the city demonstrates its technique viability and significant localization accuracy improvement compared with GPS and other approaches: the error is approximately 20m for 90% of time while the known mean error of GPS is 42.22m.

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Tang JFu LLong FWang XChen GZhou C(2024)Which Link Matters? Maintaining Connectivity of Uncertain Networks Under Adversarial AttackIEEE Transactions on Mobile Computing10.1109/TMC.2023.324862923:3(2039-2053)Online publication date: Mar-2024
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Liu ZLiu JXu XWu K(2024) DeepGPS : Deep Learning Enhanced GPS Positioning in Urban Canyons IEEE Transactions on Mobile Computing10.1109/TMC.2022.320824023:1(376-392)Online publication date: Jan-2024
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SmartLoc: push the limit of the inertial sensor based metropolitan localization using smartphone
1. Information systems
  1. Information systems applications

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Published In

MobiCom '13: Proceedings of the 19th annual international conference on Mobile computing & networking

September 2013

504 pages

ISBN:9781450319997

DOI:10.1145/2500423

General Chair:
Sumi Helal
University of Florida, USA
,
Program Chairs:
Ranveer Chandra
Microsoft, USA
,
Robin Kravets
University of Illinois, Urbana-Champaign, USA

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 30 September 2013

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MobiCom'13

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SIGMOBILE

MobiCom'13: The 19th Annual International Conference on Mobile Computing and Networking

September 30 - October 4, 2013

Florida, Miami, USA

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MobiCom '13 Paper Acceptance Rate 28 of 207 submissions, 14%;

Overall Acceptance Rate 440 of 2,972 submissions, 15%

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Study of Zero Velocity Update for Both Low-and High-Speed Human Activities

Support vector machines for young and older gait classification using inertial sensor kinematics at minimum toe clearance

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