DocumentCode :
1791727
Title :
Human activity recognition in big data smart home context
Author :
Azzi, Sabrina ; Dallaire, Cindy ; Bouzouane, Abdenour ; Bouchard, Bruno ; Giroux, Sylvain
Author_Institution :
Dept. of Math. & Comput. Sci., Univ. of Quebec at Chicoutimi, Chicoutimi, QC, Canada
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
1
Lastpage :
8
Abstract :
In smart homes, a few millions of data are sent by different sensors and RFID per day. It thus constitutes a Big Data warehouse with all the problems that come from and in our work, we are interested in the problem of managing huge data in streaming. In this paper, we propose to use very fast decision tree(VFDT) for activity recognition. We formulate Activity Recognition as a classification problem where classes correspond to activities. The performance of the VFDT and other classifiers is compared.
Keywords :
Big Data; data mining; data warehouses; decision trees; gesture recognition; home automation; radiofrequency identification; Big Data smart home context; Big Data warehouse; RFID; VFDT; human activity recognition; very fast decision tree; Algorithm design and analysis; Big data; Data mining; Decision trees; Intelligent sensors; Smart homes; Big data; activity recognition; data mining; smart home;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2014 IEEE International Conference on
Conference_Location :
Washington, DC
Type :
conf
DOI :
10.1109/BigData.2014.7004406
Filename :
7004406
Link To Document :
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