The KIPS Transactions:PartA (정보처리학회논문지A)

Korea Information Processing Society (한국정보처리학회)
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A Research on a Context-Awareness Middleware for Intelligent Homes

지능적인 홈을 위한 상황인식 미들웨어에 대한 연구

  • 최종화 (세종대학교 대학원 컴퓨터공학부) ;
  • 최순용 (세종대학교 대학원 컴퓨터공학부) ;
  • 신동규 (세종대학교 컴퓨터공학과) ;
  • 신동일 (세종대학교 컴퓨터공학과)
  • Published : 2004.12.01
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Abstract

Smart homes integrated with sensors, actuators, wireless networks and context-aware middleware will soon become part of our daily life. This paper describes a context-aware middleware providing an automatic home service based on a user's preference. The context-aware middle-ware utilizes 6 basic data for learning and predicting the user's preference on the multimedia content : the pulse, the body temperature, the facial expression, the room temperature, the time, and the location. The six data sets construct the context model and are used by the context manager module. The log manager module maintains history information for multimedia content chosen by the user. The user-pattern learning and pre-dicting module based on a neural network predicts the proper home service for the user. The testing results show that the pattern of an in-dividual's preferences can be effectively evaluated and predicted by adopting the proposed context model.

무선네트워크와 각종 감지 센서로 통합된 스마트 홈은 우리의 삶의 일부분으로 자리 잡을 것이다. 이 논문은 사용자의 선호도에 근거하여 자동적인 흠 서비스를 제공하는 상황인식 미들웨어에 대하여 설명한다. 상황인식 미들웨어는 사용자의 선호도에 대한 학습과 예측 알고리즘을 수행하기 위하여 6가지의 기본 데이터를 이용하고 제시되는 6가지의 기본 데이터는 맥박, 체온, 얼굴표정, 실내온도, 시간, 사용자 위치이다. 6개의 데이터는 컨텍스트 모델을 구성하고 컨텍스트 매니저 모듈에 의해 기본 데이터로 사용된다. 사용자에 의해서 선택되어진 컨텐츠에 대한 정보를 유지하는 로그매니저가 제시되고 사용자에게 적절한 홈서비스를 제공하기 위해 신경망에 근거한 학습 및 예측 알고리즘을 제시한다. 실험결과는 개인의 선호도 패턴이 연구된 컨텍스트 모델에 의해서 효과적으로 예측되고 평가되는 것을 보여준다.

Keywords

References

  1. Y. Rasheed, J. Edwards, C. Tai, 'Home Interoperbility Frameworks for the Digital Home,' Intel Technology Journal, 2002
  2. M. H. Sherif, 'Intelligent homes, A new Challenge in telecommunications standardization,' Communications Magazine, IEEE, Vol.40, Issue.1, 2002 https://doi.org/10.1109/MCOM.2002.978045
  3. Intelligent Home, http://www.ad.siemens.de/intelligent-home/html_76/home/home.htm
  4. G. D. Abowd, A. K. Dey, P. J. Brown, et al., 'Towards a better understanding of context and context-awareness,' Proceedings of the First International Symposium on Handheld and Ubiquitous Computing HUC'99, Lecture Notes in Computer Science, Vol.1707, 1999
  5. B. Brumitt, J. Krumm and S. Shafer, 'Ubiquitous computing & the role of geometry,' IEEE Personal Communications, pp.41-43, 2000
  6. I. A. Essa, 'Ubiquitous sensing for smart and aware environments : technologies towards the building of an aware home,' In Position Paper for the DARPA/NSF/NIST workshop on Smart Environment, 1999
  7. M. C. Mozer, 'The neural network house: An environment that adapts to its inhabitants,' In Proceedings of International Symposium on Handheld and Ubiquitous Computing, 2000
  8. The MavHome Smart Home Project, http://mavhome.uta.edu/information.html
  9. D. J. Cook, M. Youngblood, E. Heierman, K. Gopalratnam, S. Rao, A. Litvin, and F. Khawaja, 'MavHome : An Agent Based Smart Home,' Proceedings of the IEEE International Conference on Pervasive Computing and Communications, pp.521 -524, 2003 https://doi.org/10.1109/PERCOM.2003.1192783
  10. A. Roy, S. K. Das Bhaumik, A. Bhattacharya, K. Basu, D. J. Cook, S. K. Das, 'Location aware resource management in smart homes,' Proceedings of the IEEE International Conference on Pervasive Computing and Communications, pp.481-488, 2003
  11. D. J. Cook, M. Youngblood, E. O. III Heierman, K. Gopalratnam, S. Rao, A. Litvin, F. Khawaja, 'MavHome : an agent based smart home,' Proceedings of the IEEE International Conference on Pervasive Computing and Communications, pp.521-524, 2003
  12. N. Noury, G. Virone, P. Barralon, J. Ye, V. Rialle, J. Demongeot, 'New trends in health smart homes,' Proceedings of the Enterprise Networking and Computing in Healthcare Industry, pp.1l8-227, 2003
  13. Future Home Project, http://www.cordis.lu/ist
  14. Internet Protocol Version 6, http://www.ipv6.org
  15. P. Peursum, S. Venkatesh, G. A. W. West, H. H. Bui, 'Object labeling from human action recognition,' Proceedings of the IEEE International Conference on Pervasive Computing and Communications, pp.399-406, 2003
  16. C. Nebauer, 'Evaluation of convolutional neural networks for visual recognition,' Neural Networks, IEEE Transactions on, Vol.9, Issue.4, pp.685-696, 1998 https://doi.org/10.1109/72.701181
  17. S. Morishima, H. Harashima, 'Emotion space for analysis and synthesis of facial expression,' Robot and Human Communication, pp.188-193, 1993 https://doi.org/10.1109/ROMAN.1993.367724
  18. J. Nicholson, K. Takahashi, R. Nakatsu, 'Emotion recognition in speech using neural networks,' Neural Information Processing, Vol.2, pp.495-501, 1999 https://doi.org/10.1109/ICONIP.1999.845644
  19. Darwin. Charles, 'The expression of the emotions in man and animals,' Electronic Text Center, University of Virginia Library
  20. C. S. Yoon, 'Establishing the Comfort Zone of Thermal Environment in Winter,' 대한가정학회지, Vol.30, No.2, 1992
  21. Z. Chen, Y. An, K. Jia, C. Sun, 'Intelligent control of alternative current permanent manage servomotor using neural network,' Electrical Machines and Systems, Vol.2, 2001
  22. T. Bray, J. Paoli and C. M. Sperberg-McQueen, Extensible Markup Language. Recommendation, http://www.w3c.org/TR/1998/REC-xml-19980210, World Wide Web Consortium, 1998
  23. S. M. Weiss, C. A. Kulikowski, Computer Systems that Learn, Morgan Kaufmann Publishers, 1991
  24. K. M. Lin, C. J. Lin, 'A study on reduced support vector machines,' Neural Networks, IEEE Transaction on, Vol.14, Issue 6, pp.1449-1459, 2003 https://doi.org/10.1109/TNN.2003.820828

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