Online Path Description Learning Based on IMU Signals From IoT Devices

doi:10.1109/TMC.2024.3406436

科研成果详情

题名	Online Path Description Learning Based on IMU Signals From IoT Devices
作者	Zhuo，Weipeng1 ; Li，Shiju 2,3; He，Tianlang 4; Liu，Mengyun 5; Chan，S. H.Gary 4; Ha，Sangtae 6; Lee，Chul Ho 7
发表日期	2024
发表期刊	IEEE Transactions on Mobile Computing
ISSN/eISSN	1536-1233
卷号	23 期号:12 页码:11889-11906
摘要	A user's movement path can be precisely and concisely described as a concatenation of straight lines having the user's turns as their end points. Learning such a path description or representation from inertial measurement unit (IMU) sensors enables various mobile and IoT applications, as it allows efficient processing of the movement path data. It is, however, non-trivial to learn a succinct yet accurate path description from IMU sensor readings in the mobile device of a moving user on the fly due to the dynamically changing behaviors and the technical difficulty in detecting the user's turns. We propose PATHLIT, a novel online path description learning system based on IMU signals. PATHLIT learns position vectors of a user from IMU sensor readings by our custom-made self-attention network model. Once each position vector is learned, PATHLIT also decides whether or not to take it as a part of the resulting path description by our efficient online algorithm developed under the minimum description length principle, which essentially detects the user's turns along the path. We conduct extensive experiments on two large datasets. The experiment results show that PATHLIT achieves superior performance over state-of-the-art algorithms by up to 50% in absolute trajectory error using only 15% of trajectory data points.
关键词	IMU minimum description length online turn detection path recovery
DOI	10.1109/TMC.2024.3406436
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-85194887721
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/13681
专题	北师香港浸会大学
作者单位	1.BNU-HKBU United International College,Guangdong Provincial Key Laboratory IRADS,Department of Computer Science,Zhuhai,519088,China 2.Texas State University,San Marcos,78666,United States 3.Florida Institute of Technology,Texas State University,Department of Computer Engineering and Sciences,Melbourne,32901,United States 4.Hong Kong University of Science and Technology,Department of Computer Science and Engineering,Hong Kong,Hong Kong 5.Guangzhou University,Institute of Artificial Intelligence,Guangzhou,511370,China 6.University of Colorado Boulder,Department of Computer Science,Boulder,80309,United States 7.Texas State University,Department of Computer Science,San Marcos,78666,United States
第一作者单位	北师香港浸会大学
推荐引用方式 GB/T 7714	Zhuo，Weipeng,Li，Shiju,He，Tianlanget al. Online Path Description Learning Based on IMU Signals From IoT Devices[J]. IEEE Transactions on Mobile Computing, 2024, 23(12): 11889-11906.
APA	Zhuo，Weipeng., Li，Shiju., He，Tianlang., Liu，Mengyun., Chan，S. H.Gary., .. & Lee，Chul Ho. (2024). Online Path Description Learning Based on IMU Signals From IoT Devices. IEEE Transactions on Mobile Computing, 23(12), 11889-11906.
MLA	Zhuo，Weipeng,et al."Online Path Description Learning Based on IMU Signals From IoT Devices". IEEE Transactions on Mobile Computing 23.12(2024): 11889-11906.