A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone

Jhen Kai Liao, Kai-Wei Chiang, Guang Je Tsai, Hsiu-Wen Chang

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

3 Citations (Scopus)

Abstract

With the great international popularity and various sensors embedded, smartphone becomes an excellent mobile and indoor navigator. Pedestrian Dead Reckoning (PDR) is one of the most common technologies for pedestrian and indoor navigation which is based upon pedometer and orientation sensor. But various errors tend to accumulated step by step in its present form. Therefore, this study proposes a novel map aided Fuzzy Decision Tree (FDT) without complex algorithm and individually tuning process to reduce the accumulated error, improve the generation ability and minimize the use of infrastructure. The rule-based FDT algorithm estimates the location based upon the map, sensors and expert knowledge after training once then for other new experiments. Various scenarios consisted of different test sites, smartphones and users are implemented in order to verify the performance of proposed algorithm. The results verify that once the proposed algorithm is well trained, it is able to maintain good position performance regardless of the users, fields and smartphones. In addition, the positioning solution can output the global coordinate because of the use of self-produced map for seamless navigation in both indoor and outdoor environments.

Original languageEnglish
Title of host publication2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509024254
DOIs
Publication statusPublished - 2016 Nov 14
Event2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 - Madrid, Spain
Duration: 2016 Oct 42016 Oct 7

Publication series

Name2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016

Other

Other2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016
CountrySpain
CityMadrid
Period16-10-0416-10-07

Fingerprint

Fuzzy Decision Tree
Smartphones
Decision trees
navigation
Low Complexity
Navigation
Sensor
Verify
Dead Reckoning
sensors
Sensors
dead reckoning
navigators
Tree Algorithms
Positioning
Tuning
Infrastructure
Tend
positioning
Minimise

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Control and Optimization
  • Instrumentation

Cite this

Liao, J. K., Chiang, K-W., Tsai, G. J., & Chang, H-W. (2016). A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone. In 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 [7743640] (2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPIN.2016.7743640
Liao, Jhen Kai ; Chiang, Kai-Wei ; Tsai, Guang Je ; Chang, Hsiu-Wen. / A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone. 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. (2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016).
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abstract = "With the great international popularity and various sensors embedded, smartphone becomes an excellent mobile and indoor navigator. Pedestrian Dead Reckoning (PDR) is one of the most common technologies for pedestrian and indoor navigation which is based upon pedometer and orientation sensor. But various errors tend to accumulated step by step in its present form. Therefore, this study proposes a novel map aided Fuzzy Decision Tree (FDT) without complex algorithm and individually tuning process to reduce the accumulated error, improve the generation ability and minimize the use of infrastructure. The rule-based FDT algorithm estimates the location based upon the map, sensors and expert knowledge after training once then for other new experiments. Various scenarios consisted of different test sites, smartphones and users are implemented in order to verify the performance of proposed algorithm. The results verify that once the proposed algorithm is well trained, it is able to maintain good position performance regardless of the users, fields and smartphones. In addition, the positioning solution can output the global coordinate because of the use of self-produced map for seamless navigation in both indoor and outdoor environments.",
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Liao, JK, Chiang, K-W, Tsai, GJ & Chang, H-W 2016, A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone. in 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016., 7743640, 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016, Institute of Electrical and Electronics Engineers Inc., 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016, Madrid, Spain, 16-10-04. https://doi.org/10.1109/IPIN.2016.7743640

A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone. / Liao, Jhen Kai; Chiang, Kai-Wei; Tsai, Guang Je; Chang, Hsiu-Wen.

2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7743640 (2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016).

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

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AB - With the great international popularity and various sensors embedded, smartphone becomes an excellent mobile and indoor navigator. Pedestrian Dead Reckoning (PDR) is one of the most common technologies for pedestrian and indoor navigation which is based upon pedometer and orientation sensor. But various errors tend to accumulated step by step in its present form. Therefore, this study proposes a novel map aided Fuzzy Decision Tree (FDT) without complex algorithm and individually tuning process to reduce the accumulated error, improve the generation ability and minimize the use of infrastructure. The rule-based FDT algorithm estimates the location based upon the map, sensors and expert knowledge after training once then for other new experiments. Various scenarios consisted of different test sites, smartphones and users are implemented in order to verify the performance of proposed algorithm. The results verify that once the proposed algorithm is well trained, it is able to maintain good position performance regardless of the users, fields and smartphones. In addition, the positioning solution can output the global coordinate because of the use of self-produced map for seamless navigation in both indoor and outdoor environments.

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Liao JK, Chiang K-W, Tsai GJ, Chang H-W. A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone. In 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7743640. (2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016). https://doi.org/10.1109/IPIN.2016.7743640