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Autor
Lynggaard Per (Aalborg University Copenhagen, Denmark)
Tytuł
Distributed Smart Home Activity Recommender System using Hidden Markov Model Principles
Źródło
Zeszyty Naukowe Uniwersytetu Szczecińskiego. Ekonomiczne Problemy Usług, 2013, nr 104, s. 359-369, rys., bibliogr. 11 poz.
Tytuł własny numeru
Europejska przestrzeń komunikacji elektronicznej. T. 1
Słowa kluczowe
Systemy rozproszone, Ukryty model Markowa
Systems diffuse, Hidden Markov model
Uwagi
summ.
Abstrakt
A distributed smart home system has been presented. It offers a concept that combines a simple low level activity classifier named SHS-I with a high level one named SHS-II that is the target for this paper. By using the public available CASAS data set it was found that the presented system behaves well compared to the CBR and ASBR systems. It achieves a true positive rate of 75% in the "leave home" scenario.However, it should be noted that the threshold limit values are set manually, so further investigation is needed to clarify whether these limits are useable beyond the leave home scenario. The future perspective of this work is to investigate the possibility of implementing SHS-II on different hardware platforms. Furthermore, an investigation of the look back depth in the SHS-II action buffer also needs investigation.(original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Biblioteka Główna Uniwersytetu Szczecińskiego
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Bibliografia
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  1. Balasubramanian K. and Cellatoglu A.: Improvements in home automation strategies for designing apparatus for efficient smart home, Consumer Electronics, IEEE Transactions on, Vol. 54, No. 4, 2008
  2. Perumal T., Rmali A.R., and Chui Y.L.: Interoperability Framework for Smart Home Systems, IEEE Transactions on Consumer Electronics, Vol. 57, No. 4, 2011
  3. Starsinic M.: System Architecture Challenges in the Home M2M Networks, in Applications and Technology Conference (LISAT), Long Island Systems, 2010.
  4. Bhardwaj S., Ozcelebi T., Lukkien J., and Uysal C.: Resource and Service Management Architecture of a Low Capacity Network for Smart Spaces, IEEE Transactions on Consumer Electronics, Vol. 58, No. 2, 2012.
  5. Ye X., and Huang J.: A Framework for Cloud-based Smart Home, International Conference on Computer Science and Network Technology, 2011
  6. Kasteren T.V., Noulas A., Englebienne G., and Kröse B.: Accurate Activity Recognition in a Home Setting, UbiComp '08, September 21-24, Seoul, Korea.,2008
  7. Fang H., Srinivasan R., and Cook D.J.: Feature Selections for Human Activity Recognition in Smart Home Environments, International Journal of Innovative Computing, Information and Control, Vol. 8, No. 5, May 2012
  8. Cook D.J.: Learning Setting-Generalized Activity Models for Smart Spaces, Intellligent Systems IEEE, Vol. 27, No. 1, 2012.
  9. Cook D.J.: Learning Setting-Generalized Activity Models for Smart Spaces, IEEE Intelligent Systems, Vol. 27, No. 1, 2012.
  10. Fang H., Srinivasan R., and Cook D.J.: Feature Selections for Human Activity Recegnition, International Journal of Innovative Computing, Information and Control, Vol. 8, No. 5, 2012
  11. Sheng Ch.-T., Wang Ch.H., and Chen Ch.-Ch.: An Adaptive Scenario Based Reasoning System cross smart houses, Communications and Information Technologies, 2009
Cytowane przez
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ISSN
1640-6818
1896-382X
Język
pol
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