Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
권호 표지
DOI QR코드

DOI QR Code

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
Download PDF
⟨ Previous Next ⟩

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

  1. Kyung-Ae Cha, SunDong Yeo, "Smart phone Application Development for Aware of Unexpected Conditions using Accelerometer Sensors", J Korea Industr Inf Syst Vol 17, No.5, pp.1-8, 2012. https://doi.org/10.9723/jksiis.2012.17.5.001
  2. Kyung-Ae Cha, Sung-Young Hyun, "Implementation of Android application to judge the daily route deviation via the GPS information on smart phones", J Korea Industr Inf Syst Res Vol 18, No.3, pp.27-34, 2013. https://doi.org/10.9723/jksiis.2013.18.3.027
  3. Bill N. Schilit and Marvin M. Theimer, "Disseminating Active Map Information to Mobile Hosts", IEEE Network.September/ October, pp22-32, 1994.
  4. S.Y Lim, J.D Huh, "Technology Trends of Context Aware Computing Application", Electronics and Telecommunication Trends, Vol 19, No.5, pp. 31-40, 2004.
  5. D. Tancharoen, T. Ymasaki, and K. Aizawa, "Practical Experience Recording and Indexing of Life Log Video", CARPE 2005, Singapor, pp.61-66, 2005.
  6. Jim Gemmell, Gordon Bell and Roger Lueder "MyLifeBits:A Personal Database for Everything," Communications of the ACM, Vol 49, No.1, pp.88-95, 2006.
  7. Ricardo Couto Antunes da Rocha and Markus Endler, "Supporting Context-Aware Applications : Scenarios, Models and Architecture", Monografias em Ciencia da Computacao, No. 12/06, pp. 1-15, 2006.
  8. Young-wan Jang, Byeong Man Kim, Chang Bae Moon, Yoon Sik Shin, "Auto Tagging Using Mobile-Based User's Context Information for Personal Lifelog", Journal of KIISE : Computer Systems and Theory Vol 40, No.5, pp.236-247, 2013.
  9. Emiliano Miluzzo, Nicholas D.Lane, Kristof Fodor, Ronald Peterson, Hong Lu, Micro Musolesi, Shane B.Eisenman, Xiao Zheng, Andrew T.Campbell, "Sensing Meets Mobile Social Networks: The Design, Implementation and Evalution of the CenceMe Application," the 6th ACM conference on Embedded network sensor systems, pp.337-350, 2008.
  10. Hyekyung Yang, Hwangseung Young, "Physical Activity Recognition using Accelerometer of Smart Phone," Proc. of the Korea Computer Congress 2012, Vol 39, No.2(D), pp.7-9, 2012.
  11. Phil Hwan Jung, Dae young Kim, Chang geun Song, Seon woo Lee, "Recognition of Walking Behavior and Phone's Pose by using smart phones," Proc. of the Korea Computer Congress 2012, Vol 39, No.1(D), pp.124-125, 2012.
  12. Manhyung Han, Sungyoung Lee, "Personalized Activity Modeling and Real-time Activity Recognition based on Smartphone Multimodal Sensors," Journal of KIISE : Software and Applications Vol 40, No.6, pp.332-341, 2013.
  13. Muhammad Shoaib, Hans Scholtem, P.J.M. Havinga, "Towards Physical Activity Recognition Using Smartphone Sensors," 2013 IEEE 10th International Conference on Ubiquitous Intelligence & Computing and 2013 IEEE 10th International Conference on Autonomic & Trusted Computing, pp.80-87, 2013.
  14. Min-Sung Hong and Nam-Hee Mok, "A method of determinig the user's state of movement based on the smart device usage," J Korea Industr Inf Syst Res Vol 18, No.6, pp.51-59, 2013. https://doi.org/10.9723/jksiis.2013.18.6.051
  15. Google Developer [Online]. Available : http://developer.android.com/reference/android/hardware/SensorEvent.html
  16. Astronote [Online].Available : http://www.astronote.org/bbs/board.php?bo_table=prog&wr_id=18065&page=7

Cited by

  1. A user behavior prediction technique using mobile-based Lifelog vol.19, pp.6, 2014, https://doi.org/10.9723/jksiis.2014.19.6.063