Mining frequent trajectory patterns for activity monitoring using radio frequency tag arrays

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Mining frequent trajectory patterns for activity monitoring using radio frequency tag arrays (2007)

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by Yunhao Liu , Lei Chen , Jian Pei , Qiuxia Chen , Yiyang Zhao

Venue:	In Percom
Citations:	47 - 9 self

BibTeX

@INPROCEEDINGS{Liu07miningfrequent,
    author = {Yunhao Liu and Lei Chen and Jian Pei and Qiuxia Chen and Yiyang Zhao},
    title = {Mining frequent trajectory patterns for activity monitoring using radio frequency tag arrays},
    booktitle = {In Percom},
    year = {2007}
}

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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. 1.

Keyphrases

activity monitoring frequent trajectory pattern radio frequency tag array rfid technology challenging problem many application large field critical role novel application multiple camera rf tag data empirical study mine frequent trajectory pattern crucial task data mining technique rf tag attractive solution video camera real rfid system regular activity low cost data set rf tag array tracking object practical fault-tolerant method

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