NDLI: WTrack: HMM-based walk pattern recognition and indoor pedestrian tracking using phone inertial sensors

Content Provider	Springer Nature Link
Author	Niu, Xiaoguang Li, Meng Cui, Xiaohui Liu, Jin Liu, Shubo Chowdhury, Kaushik R.
Copyright Year	2014
Abstract	Indoor tracking systems have become very popular, wherein pedestrian movement is analyzed in a variety of commercial and secure spaces. The inertial sensor-based method makes great contributions to continuous and seamless indoor pedestrian tracking. However, such a system is vulnerable to the cumulative locating errors when moving distance increases. Inaccurate heading values caused by the interference of body swing of natural walking and the geomagnetic disturbances are the main sources of the accumulative errors. To reduce such errors, additional infrastructure or highly accurate sensors have been used by previous works that considerably raise the complexity of the architecture. This paper presents an indoor pedestrian tracking system called WTrack, using only geomagnetic sensors and acceleration sensors that are commonly carried by smartphones. A fine-grained walk pattern of indoor pedestrians is modeled through Hidden Markov Model. With this model, WTrack can track indoor pedestrians by continuously recognizing the pre-defined pedestrians’ walk pattern. More importantly, WTrack is able to resist both the interference of body swing of natural walking and the geomagnetic disturbances of nearby objects. Our experimental results reveal that the location error is <2 m, which is considered adequate for indoor location-based-service applications. The adaptive sample rate adjustment mode further reduces the energy consumption by 52 % in comparison, as opposed to the constant sampling mode.
Starting Page	1901
Ending Page	1915
Page Count	15
File Format	PDF
ISSN	16174909
Journal	Personal Technologies
Volume Number	18
Issue Number	8
e-ISSN	16174917
Language	English
Publisher	Springer London
Publisher Date	2014-08-09
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Indoor pedestrian tracking Walk pattern recognition Smartphone Inertial sensing Ubiquitous computing User Interfaces and Human Computer Interaction Computer Science Personal Computing
Content Type	Text
Resource Type	Article
Subject	Management Science and Operations Research Library and Information Sciences Computer Science Applications Hardware and Architecture

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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