Earticle

초록

영어

Context-awareness is an important characteristic of smart home. Several methods are used in context-aware application to provide services. The main target of smart home is to predict the demand of home users and proactively provide the proper services by computing user’s context information. In this paper, we present a context-aware application which can provide service according to predefined choice of user. It uses Mahalanobis distance based k nearest neighbors classifier technique for inference of predefined service. We combine the features of supervised and unsupervised machine learning in the proposed application. This application can also adapt itself when the choice of user is changed by using Q-learning reinforcement learning algorithm.

목차

Abstract
 1. Introduction
 2. Proposed Method
  2.1 Context Receiver Module:
  2.2 Service-triggering Context Module:
  2.3 Service Form-changing Context Module:
  2.4 Learning and Mapping:
  2.5 Inference Engine:
  2.6 Service Provider Module:
  2.7 Service Execution Module:
  2.8 Adaption Module:
  2.9 User Feedback Module:
  2.10 Knowledge Base:
 3. The Implementation Environment
 4. Conclusion
 Acknowledgements
 References

키워드

저자

• M. Humayun Kabir [ Department of Electronic Engineering, Kwangwoon University Seoul, Republic of Korea ]
• M. Robiul Hoque [ Department of Electronic Engineering, Kwangwoon University Seoul, Republic of Korea ]
• Sung-Hyun Yang [ Department of Electronic Engineering, Kwangwoon University Seoul, Republic of Korea ] Corresponding Author

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