NDLI: DREAR - Towards Infrastructure-Free Indoor Localization via Dead-Reckoning Enhanced with Activity Recognition

Content Provider	IEEE Xplore Digital Library
Author	Torok, A. Nagy, A. Kovats, L. Pach, P.
Copyright Year	2014
Description	Author affiliation: Bay Zolten Nonprofit Ltd. for Appl. Res., Budapest, Hungary (Torok, A.; Nagy, A.; Kovats, L.; Pach, P.)
Abstract	The recent indoor localization techniques use inertial sensors for position estimations in order to obtain a certain degree of freedom from infrastructure based solutions. Unfortunately, this dependency cannot be completely eliminated due to the cumulative errors induced in the localization process. While many methods are designed to reduce the required number of reference points or try to offer unsupervised maintenance, completely infrastructure independent solutions are still missing. In this paper we propose a novel approach for mobile-based indoor localization and navigation services by introducing a context-aware localization framework. We exploit the ability to recognize certain human motion patterns with a smartphone, representing activities related to walking, climbing stairs, taking escalators, etc. This allows the detection of corridors, staircases and escalators, knowledge which can be used to create building interior related reference points. Based on these a scenario specific context interpreter controls the localization process and provides position refinement for the elimination of the cumulated errors. Using our solution the auxiliary reference points can be omitted, thus, a completely infrastructure-free localization system is formed. The proposed solution is evaluated in a subway scenario and its performance is analysed focusing on the influence of dead-reckoning error on path reconstruction, the effect of activity detection quality on localization performance, respectively the benefits of using additional context-related information. The results are promising, our solution presents good localization and path reconstruction performance, showing potential for real-world scenarios, where the deployment of auxiliary localization infrastructure is unfeasible.
Starting Page	106
Ending Page	111
File Size	495493
Page Count	6
File Format	PDF
e-ISBN	9781479950737
DOI	10.1109/NGMAST.2014.47
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-10
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Legged locomotion activity detection sensor fusion algorithms Navigation Hidden Markov models Mobile communication context-aware systems indoor localization Trajectory Sensors
Content Type	Text
Resource Type	Article

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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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