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Locating using prior information: wireless indoor localization algorithm

Published: 27 August 2013 Publication History

Abstract

Most indoor localization algorithms are based on Received Signal Strength (RSS), in which RSS signatures of an interested area are annotated with their real recorded locations. However, according to our experiments, RSS signatures are not suitable as the unique annotations (like Fingerprints) of recorded locations. In this study, we investigate the characteristics of RSS (e.g., how the RSS values change as time goes on and between consecutive positions?). On this basis, we design LuPI (Locating using Prior Information) that exploits the characteristics of RSS: with user motion, LuPI uses novel sensors integrated in smartphones to construct the RSS variation space (like radio map) of a floor plan as prior information. The deployment of LuPI is easy and rapid since little human intervention is needed. In LuPI, the calibration of ``radio map'' is crowd-sourced, automatic and scheduled. Experimental results show that LuPI achieves comparable location accuracy to previous approaches, even without the statistical information of site survey.

References

[1]
K. Chintalapudi, A. Padmanabha, and V. Padmanabhan. Indoor Localization Without the Pain. In Proc. of the ACM Int. Conf. on Mobile Computing and Networking (MobiCom), 2010.
[2]
D. Turner, S. Savage, and A. Snoeren. On the Empirical Performance of Self-Calibrating WiFi Location Systems. In IEEE Conf on Local Computer Networks (LCN, 2011.
[3]
Z. Yang, C. Wu, and Y. Liu. Locating in Fingerprint Space: Wireless Indoor Localization with little Human Intervention. In Proc. of the ACM Int. Conf. on Mobile Computing and Networking (MobiCom), 2012.

Cited By

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  • (2018)Experiences & Challenges with Server-Side WiFi Indoor Localization Using Existing InfrastructureProceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3286978.3286989(226-235)Online publication date: 5-Nov-2018
  • (2016)Treasures status monitoring based on dynamic link-sensingPeer-to-Peer Networking and Applications10.1007/s12083-016-0508-610:3(780-794)Online publication date: 18-Oct-2016
  • (2014)INBS: An Improved Naive Bayes Simple learning approach for accurate indoor localization2014 IEEE International Conference on Communications (ICC)10.1109/ICC.2014.6883310(148-153)Online publication date: Jun-2014
  • Show More Cited By

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Published In

cover image ACM Conferences
SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
August 2013
580 pages
ISBN:9781450320566
DOI:10.1145/2486001
  • cover image ACM SIGCOMM Computer Communication Review
    ACM SIGCOMM Computer Communication Review  Volume 43, Issue 4
    October 2013
    595 pages
    ISSN:0146-4833
    DOI:10.1145/2534169
    Issue’s Table of Contents
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

Publication History

Published: 27 August 2013

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Author Tags

  1. floor plan
  2. indoor localization
  3. smart devices
  4. wireless networks

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  • Demonstration

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SIGCOMM'13
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SIGCOMM'13: ACM SIGCOMM 2013 Conference
August 12 - 16, 2013
Hong Kong, China

Acceptance Rates

SIGCOMM '13 Paper Acceptance Rate 38 of 246 submissions, 15%;
Overall Acceptance Rate 462 of 3,389 submissions, 14%

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Cited By

View all
  • (2018)Experiences & Challenges with Server-Side WiFi Indoor Localization Using Existing InfrastructureProceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3286978.3286989(226-235)Online publication date: 5-Nov-2018
  • (2016)Treasures status monitoring based on dynamic link-sensingPeer-to-Peer Networking and Applications10.1007/s12083-016-0508-610:3(780-794)Online publication date: 18-Oct-2016
  • (2014)INBS: An Improved Naive Bayes Simple learning approach for accurate indoor localization2014 IEEE International Conference on Communications (ICC)10.1109/ICC.2014.6883310(148-153)Online publication date: Jun-2014
  • (2020)Indoor Positioning System Based on Fuzzy Logic and WLAN InfrastructureSensors10.3390/s2016449020:16(4490)Online publication date: 11-Aug-2020
  • (2016)Smartphone Inertial Sensor-Based Indoor Localization and Tracking With iBeacon CorrectionsIEEE Transactions on Industrial Informatics10.1109/TII.2016.257926512:4(1540-1549)Online publication date: Aug-2016
  • (2015)Enhancing RFID indoor localization with cellular technologiesEURASIP Journal on Wireless Communications and Networking10.1186/s13638-015-0444-92015:1Online publication date: 28-Sep-2015

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