Detecting Human Behavior Models From Multimodal Observation in a Smart Home

2009 ◽  
Vol 6 (4) ◽  
pp. 588-597 ◽  
Author(s):  
O. Brdiczka ◽  
M. Langet ◽  
J. Maisonnasse ◽  
J.L. Crowley
2008 ◽  
Author(s):  
Steven Solomon ◽  
Michael van Lent ◽  
Mark Core ◽  
Paul Carpenter ◽  
Milton Rosenberg

2017 ◽  
Vol 46 (6) ◽  
pp. 985-1002 ◽  
Author(s):  
Gian Paolo Cimellaro ◽  
Fabrizio Ozzello ◽  
Alessio Vallero ◽  
Stephen Mahin ◽  
Benshun Shao

Home energy saving is very important to realize sustainable improvement. This can be achieved by designing a smart home system that provides a productive and cost-effective environment through optimization of different factors that will be explained in this paper. In this paper, an adaptive smart home system for optimal utilization of power will be designed. The system is based on genetic-fuzzy-neural networks technique, which can capture a human behavior patterns and use it to predict the user's mood. This technique will improve the intelligence of the smart home control to minimize the power losses.


Author(s):  
Tylar Murray ◽  
Eric Hekler ◽  
Donna Spruijt-Metz ◽  
Daniel E. Rivera ◽  
Andrew Raij

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 68535-68544 ◽  
Author(s):  
Wei Yang ◽  
Xiaojun Jing ◽  
Hai Huang

Sign in / Sign up

Export Citation Format

Share Document