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Improving GPS-based indoor-outdoor detection with moving direction information from smartphone

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UbiComp/ISWC'15 Adjunct: Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers

September 2015

Pages 257 - 260

https://doi.org/10.1145/2800835.2800939

Published: 07 September 2015 Publication History

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Abstract

This paper presents an improvement for GPS-based indoor-outdoor detection with moving direction information. First, we considered several features based on raw GPS satellite informationas the baseline. From the evaluation with GPS data from 19 persons, the SVM-based classifier using a combination of elevation and S/N ratio achieved over 96% accuracy for the simple 'clear' situation. Then we introduced direction information from a compass sensor to increase the detection robustness in the canyon of buildings. The second experimentation result showed the proposed method considering direction information kept almost the same accuracy of indoor-outdoor detectionin a 'canyon' situation, whereas the baseline classifier worsened accuracy by 10%.

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Cited By

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Liu WChambers TClevenger KPfeiffer KRzotkiewicz ZPark HPearson A(2024)Quantifying time spent outdoors: A versatile method using any type of global positioning system (GPS) and accelerometer devicesPLOS ONE10.1371/journal.pone.029994319:5(e0299943)Online publication date: 3-May-2024
https://doi.org/10.1371/journal.pone.0299943
Bai YHolden LKealy AZaminpardaz SChoy S(2022)A hybrid indoor/outdoor detection approach for smartphone-based seamless positioningJournal of Navigation10.1017/S037346332200019475:4(946-965)Online publication date: 26-Apr-2022
https://doi.org/10.1017/S0373463322000194
Essaid ZLorenzoni DScatena NXefraj RVecchio A(2022)Adaptive Distance Sensing in Contact Tracing Applications Through Indoor/Outdoor DetectionWireless Mobile Communication and Healthcare10.1007/978-3-031-06368-8_11(157-165)Online publication date: 7-Jun-2022
https://doi.org/10.1007/978-3-031-06368-8_11
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Index Terms

Improving GPS-based indoor-outdoor detection with moving direction information from smartphone
1. Human-centered computing

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Information & Contributors

Information

Published In

September 2015

1626 pages

ISBN:9781450335751

DOI:10.1145/2800835

General Chairs:
Kenji Mase
Nagoya University, JP
,
Marc Langheinrich
Università della Svizzera italiana (USI), CH
,
Daniel Gatica-Perez
IDIAP-EPFL, CH
,
Program Chairs:
Hans Gellersen
Lancaster University, UK
,
Tanzeem Choudhury
Cornell University
,
Koji Yatani
Univerisity of Tokyo, JP

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.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 September 2015

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Author Tags

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Poster

Conference

UbiComp '15

Sponsor:

Yahoo! Japan
SIGMOBILE
FX Palo Alto Laboratory, Inc.
ACM
Rakuten Institute of Technology
Microsoft
Bell Labs
SIGCHI
Panasonic
Telefónica
ISTC-PC

UbiComp '15: The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 7 - 11, 2015

Osaka, Japan

Acceptance Rates

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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UBICOMP '24

Sponsor:
sigchi
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The 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing

October 5 - 9, 2024

Melbourne , VIC , Australia

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Cited By

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Liu WChambers TClevenger KPfeiffer KRzotkiewicz ZPark HPearson A(2024)Quantifying time spent outdoors: A versatile method using any type of global positioning system (GPS) and accelerometer devicesPLOS ONE10.1371/journal.pone.029994319:5(e0299943)Online publication date: 3-May-2024
https://doi.org/10.1371/journal.pone.0299943
Bai YHolden LKealy AZaminpardaz SChoy S(2022)A hybrid indoor/outdoor detection approach for smartphone-based seamless positioningJournal of Navigation10.1017/S037346332200019475:4(946-965)Online publication date: 26-Apr-2022
https://doi.org/10.1017/S0373463322000194
Essaid ZLorenzoni DScatena NXefraj RVecchio A(2022)Adaptive Distance Sensing in Contact Tracing Applications Through Indoor/Outdoor DetectionWireless Mobile Communication and Healthcare10.1007/978-3-031-06368-8_11(157-165)Online publication date: 7-Jun-2022
https://doi.org/10.1007/978-3-031-06368-8_11
Wang LSommer LRiedel TBeigl MZhou YHuang Y(2020)NeuralIO: Indoor Outdoor Detection via Multimodal Sensor Data Fusion on SmartphonesScience and Technologies for Smart Cities10.1007/978-3-030-51005-3_13(127-138)Online publication date: 28-Jul-2020
https://doi.org/10.1007/978-3-030-51005-3_13
Agarwal RChopra SChristophides VGeorgantas NIssarny V(2019)Detecting Mobile Crowdsensing Context in the Wild2019 20th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2019.00-60(170-175)Online publication date: Jun-2019
https://doi.org/10.1109/MDM.2019.00-60
Zhang LNi QZhai MMoreno JBriso C(2019)An Ensemble Learning Scheme for Indoor-Outdoor Classification Based on KPIs of LTE NetworkIEEE Access10.1109/ACCESS.2019.29144517(63057-63065)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2914451
Zhang LNi QZhang GZhai MMoreno JBriso C(2019)Random forests‐enabled context detections for long‐term evolution network forrailwayIET Microwaves, Antennas & Propagation10.1049/iet-map.2018.602513:8(1080-1086)Online publication date: 7-May-2019
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Wang LRoth JRiedel TBeigl MYao J(2019)AudioIO: Indoor Outdoor Detection on Smartphones via Active Sound Probing3rd EAI International Conference on IoT in Urban Space10.1007/978-3-030-28925-6_8(81-95)Online publication date: 14-Nov-2019
https://doi.org/10.1007/978-3-030-28925-6_8
Ashraf IHur SPark Y(2018)MagIO: Magnetic Field Strength Based Indoor- Outdoor Detection with a Commercial SmartphoneMicromachines10.3390/mi91005349:10(534)Online publication date: 20-Oct-2018
https://doi.org/10.3390/mi9100534
Zeng QWang JMeng QZhang XZeng S(2018)Seamless Pedestrian Navigation Methodology Optimized for Indoor/Outdoor DetectionIEEE Sensors Journal10.1109/JSEN.2017.276450918:1(363-374)Online publication date: 1-Jan-2018
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