Earticle

초록

영어

Smart homes are equipped with a variety of sensors to monitor the human activities. The information gathered from the heterogeneous sensors may not be always reliable and have different degrees of uncertainly. One of the most important techniques have been proposed to deal with uncertainty is Dempster-Shafer Theory (DST). In this paper, aims to define more precise sensor reliability and decrease uncertainty in sensor data in the activity recognition process within smart home. In the proposed method, in training step some models are built for per activity according extracted features from training samples and then in the prediction step when a new signal sensor is observed, the features extracted from that signal and applied to models and a weight is calculated for that sensor. These weights are considered as sensor reliability and uses in the decision making process.

목차

Abstract
 1. Introduction
 2. Dempster-Shafer Theory
 3. Proposed Method
 4. Simulation and results analyzing
 5. Conclusion
 References

키워드

저자

• Elham Javadi [ Department of Computer Science and Research, Islamic Azad University of Kerman, Iran ]
• Behzad Moshiri [ Control and Intelligent Processing Center of Excellence, School of ECE, University of Tehran, Tehran, Iran ]
• Hadi Sadoghi Yazdi [ Department of Computer, Ferdowsi University of Mashhad, Mashhad, Iran ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605