Earticle

초록

영어

A method of distinguishing several events included in sensor data was proposed, when various events were sensed simultaneously to the data several sensors sensed and reported and individual event data were mixed in an environment in which a data stream was sequentially obtained. This study had each sensor distinguish each event through a fast analysis of the data sensed by each sensor in this condition. For this purpose, clustering was made with sensor data, and first, internal variance of event cluster classified by each sensor was calculated, and how this changed with the passage of time was checked. Next, the cluster of each sensor sensing the same event was compared. Through this process, the sensed event could be more clearly distinguished. This study suggested the measure to divide a small quantity of sensors when it senses the several events. This measure can be used as application for the small mobile vehicle or robot to sense the peripheral situation.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Weighting Method in the Risk Recognition
  3.1. Definition of Internal Variance
  3.2 Definition of External Variance
 4. An Experiment and Evaluation
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Donghyok Suh [ Department of Architectural Engineering, Namseoul University ]
• Kunsoo Oh [ Department of Architectural Engineering, Namseoul University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605