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Poster: Online Map Matching for Passive Indoor Positioning Systems

Published: 16 June 2017 Publication History

Abstract

Passive indoor positioning systems (PIPS) enable non-invasive tracking of mobile devices (e.g., smartphones, Wi-Fi tags) using enterprise network infrastructure. This empowers operators of large airports and retail facilities to optimize cost-intensive resource allocation as well as to provide location-based services to their customers such as geo-fencing and proximity marketing. However, existing PIPS often generate noisy location estimates due to unpredictable interference and attenuation of wireless signals in indoor environments. To address this problem, we propose a novel map matching approach that uses a floor map to constrain location estimates to possible paths a mobile user can take.

References

[1]
Cisco Hyperlocation module with advanced security. http://www.cisco.com/c/en/us/products/interfaces-modules/aironet-hyperlocation-module-advanced-security/index.html.
[2]
P. Newson and J. Krumm. Hidden Markov map matching through noise and sparseness. In Proc. of the 17th ACM SIGSPATIAL, pages 336--343, 2009.

Cited By

View all
  • (2021)Towards Adaptive, Self-Configuring Networked Unmanned Aerial VehiclesProceedings of the 7th Workshop on Micro Aerial Vehicle Networks, Systems, and Applications10.1145/3469259.3470488(25-30)Online publication date: 24-Jun-2021
  • (2018)Towards Location Enhanced IoT: Characterization of LoRa Signal For Wide Area Localization2018 Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS)10.1109/UPINLBS.2018.8559844(1-7)Online publication date: Mar-2018

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Published In

cover image ACM Conferences
MobiSys '17: Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services
June 2017
520 pages
ISBN:9781450349284
DOI:10.1145/3081333
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: 16 June 2017

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Author Tags

  1. hidden Markov model
  2. map matching
  3. passive indoor positioning system

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  • Poster

Funding Sources

  • Cisco Systems, Inc.

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MobiSys'17
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Acceptance Rates

MobiSys '17 Paper Acceptance Rate 34 of 188 submissions, 18%;
Overall Acceptance Rate 274 of 1,679 submissions, 16%

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Cited By

View all
  • (2021)Towards Adaptive, Self-Configuring Networked Unmanned Aerial VehiclesProceedings of the 7th Workshop on Micro Aerial Vehicle Networks, Systems, and Applications10.1145/3469259.3470488(25-30)Online publication date: 24-Jun-2021
  • (2018)Towards Location Enhanced IoT: Characterization of LoRa Signal For Wide Area Localization2018 Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS)10.1109/UPINLBS.2018.8559844(1-7)Online publication date: Mar-2018

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