DocumentCode :
2229374
Title :
Mining Frequent Trajectory Patterns for Activity Monitoring Using Radio Frequency Tag Arrays
Author :
Liu, Yunhao ; Chen, Lei ; Pei, Jian ; Chen, Qiuxia ; Zhao, Yiyang
Author_Institution :
Hong Kong Univ. of Sci. & Technol.
fYear :
2007
fDate :
19-23 March 2007
Firstpage :
37
Lastpage :
46
Abstract :
Activity monitoring, a crucial task in many applications, is often conducted expensively using video cameras. Also, effectively monitoring a large field by analyzing images from multiple cameras remains a challenging problem. In this paper, we introduce a novel application of the recently developed RFID technology: using RF tag arrays for activity monitoring, where data mining techniques play a critical role. The RFID technology provides an economically attractive solution due to the low cost of RF tags and readers. Another novelty of this design is that the tracking objects do not need to attach any transmitters or receivers, such as tags or readers. By developing a practical fault-tolerant method, we offset the noise of RF tag data and mine frequent trajectory patterns as models of regular activities. Our empirical study using real RFID systems and data sets verifies the feasibility and the effectiveness of our design
Keywords :
data mining; fault tolerance; monitoring; radiofrequency identification; video cameras; RF tag arrays; RFID technology; activity monitoring; data mining techniques; fault-tolerant method; multiple cameras; object tracking; radio frequency tag arrays; trajectory pattern mining; video cameras; Chemical industry; Data mining; Digital cameras; Image analysis; Monitoring; Pattern analysis; Radio frequency; Radiofrequency identification; Security; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Communications, 2007. PerCom '07. Fifth Annual IEEE International Conference on
Conference_Location :
White Plains, NY
Print_ISBN :
0-7695-2787-6
Type :
conf
DOI :
10.1109/PERCOM.2007.23
Filename :
4144748
Link To Document :
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