DocumentCode :
2676584
Title :
Preference model assisted activity recognition learning in a smart home environment
Author :
Chen, Yi-Han ; Lu, Ching-Hu ; Hsu, Kuo-Chung ; Fu, Li-Chen ; Yeh, Yu-Jung ; Kuo, Lun-Chia
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fYear :
2009
fDate :
10-15 Oct. 2009
Firstpage :
4657
Lastpage :
4662
Abstract :
Reliable recognition of activities from cluttered sensory data is challenging and important for a smart home to enable various activity-aware applications. In addition, understanding a user´s preferences and then providing corresponding services is substantial in a smart home environment. Traditionally, activity recognition and preference learning were dealt with separately. In this work, we aim to develop a hybrid system which is the first trial to model the relationship between an activity model and a preference model so that the resultant hybrid model enables a preference model to assist in recovering performance of activity recognition in a dynamic environment. More specifically, on-going activity which a user performs in this work is regarded as high level contexts to assist in building a user´s preference model. Based on the learned preference model, the smart home system provides more appropriate services to a user so that the hybrid system can better interact with the user and, more importantly, gain his/her feedback. The feedback is used to detect if there is any change in human behavior or sensor deployment such that the system can adjust the preference model and the activity model in response to the change. Finally, the experimental results confirm the effectiveness of the proposed approach.
Keywords :
home automation; learning (artificial intelligence); ubiquitous computing; activity-aware applications; cluttered sensory data; context-aware applications; preference model assisted activity recognition learning; sensor deployment; smart home environment; ubiquitous computing; Cameras; Context modeling; Feedback; Hidden Markov models; Humans; Intelligent robots; Radiofrequency identification; Smart homes; USA Councils; Ubiquitous computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-3803-7
Electronic_ISBN :
978-1-4244-3804-4
Type :
conf
DOI :
10.1109/IROS.2009.5353937
Filename :
5353937
Link To Document :
بازگشت