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FALE: Fine-grained Device Free Localization that can Adaptively work in Different Areas with Little Effort

Authors:

Ju Wang,

Zhanyong TangAuthors Info & Claims

ACM SIGCOMM Computer Communication Review, Volume 45, Issue 4

Pages 601 - 602

https://doi.org/10.1145/2829988.2790020

Published: 17 August 2015 Publication History

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Abstract

Many emerging applications and the ubiquitous wireless signals have accelerated the development of Device Free localization (DFL) techniques, which can localize objects without the need to carry any wireless devices. Most traditional DFL methods have a main drawback that as the pre-obtained Received Signal Strength (RSS) measurements (i.e., fingerprint) in one area cannot be directly applied to the new area for localization, and the calibration process of each area will result in the human effort exhausting problem. In this paper, we propose FALE, a fine-grained transferring DFL method that can adaptively work in different areas with little human effort and low energy consumption. FALE employs a rigorously designed transferring function to transfer the fingerprint into a projected space, and reuse it across different areas, thus greatly reduce the human effort. On the other hand, FALE can reduce the data volume and energy consumption by taking advantage of the compressive sensing (CS) theory. Extensive real-word experimental results also illustrate the effectiveness of FALE.

References

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Yang SGuo YLi NLu A(2020)PGMP: A Device-Free Moving Object Counting and Localization Approach in the Varying EnvironmentIEEE Wireless Communications Letters10.1109/LWC.2020.29886939:8(1287-1290)Online publication date: Aug-2020
https://doi.org/10.1109/LWC.2020.2988693
Yang SGuo YLi NJiang X(2020)A Potential Orthogonal Matching Pursuit Algorithm for Device Free Moving Target LocalizationIEEE Communications Letters10.1109/LCOMM.2020.299275724:8(1691-1694)Online publication date: Aug-2020
https://doi.org/10.1109/LCOMM.2020.2992757
Guo YYang SLi NJiang X(2020)Device-Free Localization Scheme With Time-Varying Gestures Using Block Compressive SensingIEEE Access10.1109/ACCESS.2020.29935768(88951-88960)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2993576
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Index Terms

FALE: Fine-grained Device Free Localization that can Adaptively work in Different Areas with Little Effort
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing design and evaluation methods

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Information

Published In

cover image ACM SIGCOMM Computer Communication Review

ACM SIGCOMM Computer Communication Review Volume 45, Issue 4

SIGCOMM'15

October 2015

659 pages

ISSN:0146-4833

DOI:10.1145/2829988

Editors:
Konstantina Papagiannaki
Telefonica Research, Barcelona, Spain
,
Katerina Argyraki
EPFL, Switzerland
,
Hitesh Ballani
Microsoft Research Cambridge, UK
,
Fabián Bustamante
Northwestern University, USA
,
Joseph Camp
SMU, USA
,
Augustin Chaintreau
Columbia University, USA
,
Phillipa Gill
Stony Brook University, USA
,
Marco Mellia
Politecnico di Torino, Italy
,
Bhaskaran Raman
IIT Bombay, India
,
Joel Sommers
Colgate University, USA
,
Aline Carneiro Viana
INRIA, France

Issue’s Table of Contents

SIGCOMM '15: Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication
August 2015
684 pages
ISBN:9781450335423
DOI:10.1145/2785956
General Chairs:
Steve Uhlig
Queen Mary University of London, UK
,
Olaf Maennel
Tallinn U. of Technology in Estonia, Estonia
,
Program Chairs:
Brad Karp
University College London, UK
,
Jitendra Padhye
Microsoft, 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.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 August 2015

Published in SIGCOMM-CCR Volume 45, Issue 4

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Northweste University graduate student innovation training project
Project National Key Technology R&D Program,
Project NSFC,

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Cited By

View all

Yang SGuo YLi NLu A(2020)PGMP: A Device-Free Moving Object Counting and Localization Approach in the Varying EnvironmentIEEE Wireless Communications Letters10.1109/LWC.2020.29886939:8(1287-1290)Online publication date: Aug-2020
https://doi.org/10.1109/LWC.2020.2988693
Yang SGuo YLi NJiang X(2020)A Potential Orthogonal Matching Pursuit Algorithm for Device Free Moving Target LocalizationIEEE Communications Letters10.1109/LCOMM.2020.299275724:8(1691-1694)Online publication date: Aug-2020
https://doi.org/10.1109/LCOMM.2020.2992757
Guo YYang SLi NJiang X(2020)Device-Free Localization Scheme With Time-Varying Gestures Using Block Compressive SensingIEEE Access10.1109/ACCESS.2020.29935768(88951-88960)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2993576
Yang SGuo YLi NQian P(2019)Compressive Sensing Based Device-Free Multi-Target Localization Using Quantized MeasurementIEEE Access10.1109/ACCESS.2019.29204827(73172-73181)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2920482
Wang JXiong JJiang HChen XFang D(2017)D-WatchIEEE/ACM Transactions on Networking10.1109/TNET.2017.274758325:6(3559-3572)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1109/TNET.2017.2747583
Wang JFang DYang ZJiang HChen XXing TCai L(2017)E-HIPAIEEE Transactions on Mobile Computing10.1109/TMC.2016.256739616:3(716-729)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1109/TMC.2016.2567396
Wang JXiong JJiang HChen XFang DMarkopoulou AFaloutsos MSekar VKostic D(2016)D-WatchProceedings of the 12th International on Conference on emerging Networking EXperiments and Technologies10.1145/2999572.2999589(253-266)Online publication date: 6-Dec-2016
https://dl.acm.org/doi/10.1145/2999572.2999589
Yu DGuo YLi NFang D(2016)Dictionary Refinement for Compressive Sensing Based Device-Free Localization via the Variational EM AlgorithmIEEE Access10.1109/ACCESS.2017.26495404(9743-9757)Online publication date: 2016
https://doi.org/10.1109/ACCESS.2017.2649540
Chomu KAtanasovski VGavrilovska L(2017)Finding Near-Optimal Regularization Parameter for Indoor Device-free LocalizationWireless Personal Communications: An International Journal10.1007/s11277-016-3846-z92:1(197-220)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1007/s11277-016-3846-z

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FALE: Fine-grained Device Free Localization that can Adaptively work in Different Areas with Little Effort

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