International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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An indoor localization system for estimating human trajectories using a foot-mounted IMU sensor and step classification based on LSTM

  • Ts.Tengis (Dept. of Electronics, Mongolian University of Science and Technology) ;
  • B.Dorj (Dept. of Electronics, Mongolian University of Science and Technology) ;
  • T.Amartuvshin (Dept. of Electronics, Mongolian University of Science and Technology) ;
  • Ch.Batchuluun (Dept. of Electronics, Mongolian University of Science and Technology) ;
  • G.Bat-Erdene (Dept. of General Science, Mongolian National University of Medical Sciences) ;
  • Kh.Temuulen (Underground Fire protection System service team, Tavan ord LLC)
  • Received : 2024.01.19
  • Accepted : 2024.02.03
  • Published : 2024.03.31
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Abstract

This study presents the results of designing a system that determines the location of a person in an indoor environment based on a single IMU sensor attached to the tip of a person's shoe in an area where GPS signals are inaccessible. By adjusting for human footfall, it is possible to accurately determine human location and trajectory by correcting errors originating from the Inertial Measurement Unit (IMU) combined with advanced machine learning algorithms. Although there are various techniques to identify stepping, our study successfully recognized stepping with 98.7% accuracy using an artificial intelligence model known as Long Short-Term Memory (LSTM). Drawing upon the enhancements in our methodology, this article demonstrates a novel technique for generating a 200-meter trajectory, achieving a level of precision marked by a 2.1% error margin. Indoor pedestrian navigation systems, relying on inertial measurement units attached to the feet, have shown encouraging outcomes.

Keywords

Acknowledgement

The research funding was provided by the "2022/02: Agreement on implementation and financing of mining research grants" project is financed through the contract implemented based on the tripartite agreement established among 'Oyu Tolgoi' LLC, Mongolian University of Science and Technology, and 'Rio Tinto' LLC.

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