Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Learning data preprocessing technique for improving indoor positioning performance based on machine learning

기계학습 기반의 실내 측위 성능 향상을 위한 학습 데이터 전처리 기법

  • Kim, Dae-Jin (Institute for Image & Cultural Contents, Dongguk University) ;
  • Hwang, Chi-Gon (Dept. of Computer Engineering, IIT, Kwangwoon University) ;
  • Yoon, Chang-Pyo (Dept. Of Computer & Mobile Convergence, GyeongGi University of Science and Technology)
  • Received : 2020.10.13
  • Accepted : 2020.10.24
  • Published : 2020.11.30
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Abstract

Recently, indoor location recognition technology using Wi-Fi fingerprints has been applied and operated in various industrial fields and public services. Along with the interest in machine learning technology, location recognition technology based on machine learning using wireless signal data around a terminal is rapidly developing. At this time, in the process of collecting radio signal data required for machine learning, the accuracy of location recognition is lowered due to distorted or unsuitable data for learning. In addition, when location recognition is performed based on data collected at a specific location, a problem occurs in location recognition at surrounding locations that are not included in the learning. In this paper, we propose a learning data preprocessing technique to obtain an improved position recognition result through the preprocessing of the collected learning data.

최근 Wi-Fi 전파 지문을 이용한 실내 위치 인식 기술이 다양한 산업 분야 및 공공 서비스에서 적용되어 운영되고 있다. 기계학습 기술의 관심과 함께 단말 주변의 무선 신호 데이터를 사용한 기계학습 기반의 위치 인식 기술이 빠르게 발전하고 있다. 이때 기계학습에 필요한 무선 신호 데이터의 수집 과정에서 왜곡되거나 학습에 적합하지 않은 데이터가 포함되어 위치 인식의 정확도가 낮아지는 결과가 발생한다. 또한 특정 위치에서 수집된 데이터를 기반의 위치 인식을 수행하는 경우 학습에 포함되지 않은 주변 위치에서의 위치 인식에 문제가 발생한다. 본 논문에서는 수집된 학습 데이터의 전처리 과정을 통해 향상된 위치 인식 결과를 얻기 위한 학습 데이터 전처리 기법을 제안한다.

Keywords

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