PINUS: Indoor weighted centroid localization with crowdsourced calibration

Jehn Ruey Jiang, Hanas Subakti, Ching Chih Chen, Kazuya Sakai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

PINUS, an indoor weighted centroid localization (WCL) method with crowdsourced calibration, is proposed in this paper. It relies on crowdsourcing to do the calibration for WCL to improve localization accuracy without the device diversity problem. Smartphones and Bluetooth Low Energy (BLE) beacon devices are applied to realize PINUS for the sake of design validation and performance evaluation.

Original languageEnglish
Title of host publicationParallel and Distributed Computing, Applications and Technologies - 19th International Conference, PDCAT 2018, Revised Selected Papers
EditorsHong Shen, Hui Tian, Jong Hyuk Park, Yunsick Sung
PublisherSpringer Verlag
Pages433-443
Number of pages11
ISBN (Print)9789811359064
DOIs
StatePublished - 2019
Event19th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2018 - Jeju Island, Korea, Republic of
Duration: 20 Aug 201822 Aug 2018

Publication series

NameCommunications in Computer and Information Science
Volume931
ISSN (Print)1865-0929

Conference

Conference19th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2018
Country/TerritoryKorea, Republic of
CityJeju Island
Period20/08/1822/08/18

Keywords

  • Beacon
  • Bluetooth
  • Calibration
  • Crowdsourcing
  • Device diversity
  • Indoor localization
  • Weighted centroid localization

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