Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space

Chi Chung Lo, Ting Hui Chiang, Tsu Kuang Lee, Ling Jyh Chen, Yu Chee Tseng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Indoor localization systems have attracted considerable attention recently. A lot of works have used wireless signals from existing base stations to track users' locations. The major challenge to such systems is the signal-drifting problem. A promising direction to conquer this problem is to fuse the tracked wireless signals with inertial sensing data. In this work, we consider location tracking in a multi-floor building, which we call a 2.5-D space, by taking wireless signals, inertial sensing data, and indoor floor plans of a 2.5-D space as inputs and building a SPF (sensor-assisted particle filter) model to fuse these data. Inertial sensors are to capture human mobility, while particles reflect our belief of the user's potential locations. Our work makes the following contributions. First, we propose a model to partition a 2.5-D space into multiple floors connected by stairs and elevators and further partition each floor, according to its floor plan, into logical units connected by passages. Second, based on the 2.5D space model, we then propose particle sampling and resampling mechanisms over the logical units using wireless signal strengths and inertial sensing data to adjust our beliefs of the user's potential locations. Third, to conquer the signal-drifting problem, we propose a weighting mechanism to control the distribution of particles based on user's activities of walking on grounds/stairs and taking elevators. A prototype has been developed and tested to verify the model and its accuracy.

Original languageEnglish
Title of host publication2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538617342
DOIs
Publication statusPublished - 2018 Jun 8
Event2018 IEEE Wireless Communications and Networking Conference, WCNC 2018 - Barcelona, Spain
Duration: 2018 Apr 152018 Apr 18

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
Volume2018-April
ISSN (Print)1525-3511

Other

Other2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
CountrySpain
CityBarcelona
Period18/4/1518/4/18

Fingerprint

Sensors
Stairs
Elevators
Electric fuses
Partitions (building)
Base stations
Sampling

Keywords

  • Location tracking
  • Location-based service
  • Particle filter
  • Pedestrian dead-reckoning
  • Sensor network

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Lo, C. C., Chiang, T. H., Lee, T. K., Chen, L. J., & Tseng, Y. C. (2018). Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space. In 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018 (pp. 1-6). (IEEE Wireless Communications and Networking Conference, WCNC; Vol. 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WCNC.2018.8377214

Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space. / Lo, Chi Chung; Chiang, Ting Hui; Lee, Tsu Kuang; Chen, Ling Jyh; Tseng, Yu Chee.

2018 IEEE Wireless Communications and Networking Conference, WCNC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6 (IEEE Wireless Communications and Networking Conference, WCNC; Vol. 2018-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lo, CC, Chiang, TH, Lee, TK, Chen, LJ & Tseng, YC 2018, Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space. in 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018. IEEE Wireless Communications and Networking Conference, WCNC, vol. 2018-April, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018, Barcelona, Spain, 18/4/15. https://doi.org/10.1109/WCNC.2018.8377214
Lo CC, Chiang TH, Lee TK, Chen LJ, Tseng YC. Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space. In 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-6. (IEEE Wireless Communications and Networking Conference, WCNC). https://doi.org/10.1109/WCNC.2018.8377214
Lo, Chi Chung ; Chiang, Ting Hui ; Lee, Tsu Kuang ; Chen, Ling Jyh ; Tseng, Yu Chee. / Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space. 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-6 (IEEE Wireless Communications and Networking Conference, WCNC).
@inproceedings{ecaa7c3fbc8e435fbc55c8df4b933747,
title = "Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space",
abstract = "Indoor localization systems have attracted considerable attention recently. A lot of works have used wireless signals from existing base stations to track users' locations. The major challenge to such systems is the signal-drifting problem. A promising direction to conquer this problem is to fuse the tracked wireless signals with inertial sensing data. In this work, we consider location tracking in a multi-floor building, which we call a 2.5-D space, by taking wireless signals, inertial sensing data, and indoor floor plans of a 2.5-D space as inputs and building a SPF (sensor-assisted particle filter) model to fuse these data. Inertial sensors are to capture human mobility, while particles reflect our belief of the user's potential locations. Our work makes the following contributions. First, we propose a model to partition a 2.5-D space into multiple floors connected by stairs and elevators and further partition each floor, according to its floor plan, into logical units connected by passages. Second, based on the 2.5D space model, we then propose particle sampling and resampling mechanisms over the logical units using wireless signal strengths and inertial sensing data to adjust our beliefs of the user's potential locations. Third, to conquer the signal-drifting problem, we propose a weighting mechanism to control the distribution of particles based on user's activities of walking on grounds/stairs and taking elevators. A prototype has been developed and tested to verify the model and its accuracy.",
keywords = "Location tracking, Location-based service, Particle filter, Pedestrian dead-reckoning, Sensor network",
author = "Lo, {Chi Chung} and Chiang, {Ting Hui} and Lee, {Tsu Kuang} and Chen, {Ling Jyh} and Tseng, {Yu Chee}",
year = "2018",
month = "6",
day = "8",
doi = "10.1109/WCNC.2018.8377214",
language = "English",
series = "IEEE Wireless Communications and Networking Conference, WCNC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "2018 IEEE Wireless Communications and Networking Conference, WCNC 2018",

}

TY - GEN

T1 - Wireless location tracking by a sensor-assisted particle filter and floor plans in a 2.5-D space

AU - Lo, Chi Chung

AU - Chiang, Ting Hui

AU - Lee, Tsu Kuang

AU - Chen, Ling Jyh

AU - Tseng, Yu Chee

PY - 2018/6/8

Y1 - 2018/6/8

N2 - Indoor localization systems have attracted considerable attention recently. A lot of works have used wireless signals from existing base stations to track users' locations. The major challenge to such systems is the signal-drifting problem. A promising direction to conquer this problem is to fuse the tracked wireless signals with inertial sensing data. In this work, we consider location tracking in a multi-floor building, which we call a 2.5-D space, by taking wireless signals, inertial sensing data, and indoor floor plans of a 2.5-D space as inputs and building a SPF (sensor-assisted particle filter) model to fuse these data. Inertial sensors are to capture human mobility, while particles reflect our belief of the user's potential locations. Our work makes the following contributions. First, we propose a model to partition a 2.5-D space into multiple floors connected by stairs and elevators and further partition each floor, according to its floor plan, into logical units connected by passages. Second, based on the 2.5D space model, we then propose particle sampling and resampling mechanisms over the logical units using wireless signal strengths and inertial sensing data to adjust our beliefs of the user's potential locations. Third, to conquer the signal-drifting problem, we propose a weighting mechanism to control the distribution of particles based on user's activities of walking on grounds/stairs and taking elevators. A prototype has been developed and tested to verify the model and its accuracy.

AB - Indoor localization systems have attracted considerable attention recently. A lot of works have used wireless signals from existing base stations to track users' locations. The major challenge to such systems is the signal-drifting problem. A promising direction to conquer this problem is to fuse the tracked wireless signals with inertial sensing data. In this work, we consider location tracking in a multi-floor building, which we call a 2.5-D space, by taking wireless signals, inertial sensing data, and indoor floor plans of a 2.5-D space as inputs and building a SPF (sensor-assisted particle filter) model to fuse these data. Inertial sensors are to capture human mobility, while particles reflect our belief of the user's potential locations. Our work makes the following contributions. First, we propose a model to partition a 2.5-D space into multiple floors connected by stairs and elevators and further partition each floor, according to its floor plan, into logical units connected by passages. Second, based on the 2.5D space model, we then propose particle sampling and resampling mechanisms over the logical units using wireless signal strengths and inertial sensing data to adjust our beliefs of the user's potential locations. Third, to conquer the signal-drifting problem, we propose a weighting mechanism to control the distribution of particles based on user's activities of walking on grounds/stairs and taking elevators. A prototype has been developed and tested to verify the model and its accuracy.

KW - Location tracking

KW - Location-based service

KW - Particle filter

KW - Pedestrian dead-reckoning

KW - Sensor network

UR - http://www.scopus.com/inward/record.url?scp=85049178719&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049178719&partnerID=8YFLogxK

U2 - 10.1109/WCNC.2018.8377214

DO - 10.1109/WCNC.2018.8377214

M3 - Conference contribution

AN - SCOPUS:85049178719

T3 - IEEE Wireless Communications and Networking Conference, WCNC

SP - 1

EP - 6

BT - 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -