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Author
Lynggaard Per (Aalborg University Copenhagen, Denmark)
Title
Distributed Smart Home Activity Recommender System using Hidden Markov Model Principles
Source
Zeszyty Naukowe Uniwersytetu Szczecińskiego. Ekonomiczne Problemy Usług, 2013, nr 104, s. 359-369, rys., bibliogr. 11 poz.
Issue title
Europejska przestrzeń komunikacji elektronicznej. T. 1
Keyword
Systemy rozproszone, Ukryty model Markowa
Systems diffuse, Hidden Markov model
Note
summ.
Abstract
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)
Accessibility
The Main Library of Poznań University of Economics and Business
Szczecin University Main Library
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Bibliography
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  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
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ISSN
1640-6818
1896-382X
Language
pol
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