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Application of Euclidean Distance Similarity for Smartphone-Based Moving Context Determination

스마트폰 기반의 이동상황 판별을 위한 유클리디안 거리유사도의 응용

  • 장영환 (금오공과대학교 소프트웨어공학과) ;
  • 김병만 (금오공과대학교 소프트웨어공학과) ;
  • 장성봉 (금오공과대학교 소프트웨어공학과) ;
  • 신윤식 (금오공과대학교 소프트웨어공학과)
  • Received : 2014.07.25
  • Accepted : 2014.08.18
  • Published : 2014.08.30

Abstract

Moving context determination is an important issue to be resolved in a mobile computing environment. This paper presents a method for recognizing and classifying a mobile user's moving context by Euclidean distance similarity. In the proposed method, basic data are gathered using Global Positioning System (GPS) and accelerometer sensors, and by using the data, the system decides which moving situation the user is in. The decided situation is one of the four categories: stop, walking, run, and moved by a car. In order to evaluate the effectiveness and feasibility of the proposed scheme, we have implemented applications using several variations of Euclidean distance similarity on the Android system, and measured the accuracies. Experimental results show that the proposed system achieves more than 90% accuracy.

이동 컴퓨팅 환경에서 사용자 움직임 판별은 해결해야 할 중요한 이슈중의 하나이다. 본 논문에서는 유클리디안 거리 유사도를 이용하여 스마트폰 사용자의 움직임을 인식하고 판별하기 위한 방법을 제시한다. 제안된 방법에서는 GPS와 가속 센서를 이용하여 데이터를 수집하고, 수집된 데이터를 이용하여, 사용자의 정지, 걷기, 뛰기, 차량이동을 판별한다. 제안된 방법의 타당성과 효율성을 검증하기 위하여, 안드로이드 시스템에 유클리디안 거리 유사도의 여러 변형을 이용한 응용프로그램을 구현하여 그 정확도를 측정하였다. 실험 결과, 사용자 움직임 종류를 90% 이상의 정확도를 가지고 판별해 내었다.

Keywords

References

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