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A Multi-Floor Indoor Pedestrian Localization Method Using Landmarks Detection for Different Holding Styles
Author(s) -
Khanh Nguyen-Huu,
Seon-Woo Lee
Publication year - 2021
Publication title -
mobile information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.346
H-Index - 34
eISSN - 1875-905X
pISSN - 1574-017X
DOI - 10.1155/2021/6617417
Subject(s) - computer science , landmark , pedestrian , stairs , barometer , computer vision , dead reckoning , artificial intelligence , position (finance) , tracking (education) , track (disk drive) , real time computing , global positioning system , telecommunications , psychology , pedagogy , civil engineering , physics , finance , quantum mechanics , transport engineering , engineering , economics , operating system
-e pedestrian dead reckoning (PDR) technique is widely used due to its ease of implementation on portable devices such as smartphones. However, the position error that accumulates over time is the main drawback of this technology. In this paper, we propose a fusion method combining a PDR technique and the landmark recognition methods for multi-floor indoor environments using a smartphone in different holding styles. -e proposed method attempts to calibrate the position of a pedestrian by detecting whether the pedestrian passes by specific locations called landmarks.-ree kinds of landmarks are defined, which are the WiFi, the turning, and the stairs landmarks, and the detection methods for each landmark are proposed. Besides, an adaptive floor detection method using a barometer and a WiFi fingerprinting technique is suggested for tracking a pedestrian in a multifloor building. -e developed system can track the pedestrian holding a smartphone in four styles. -e results of the experiment conducted by three subjects changing the holding style in a three-floor building show the superior performance of the proposed method. It reduces the error rate of positioning results to less than 57.51% compared with the improved PDR alone system.

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