Paper
26 July 2007 Modeling and query the uncertainty of network constrained moving objects based on RFID data
Liang Han, Kunqing Xie, Xiujun Ma, Guojie Song
Author Affiliations +
Abstract
The management of network constrained moving objects is more and more practical, especially in intelligent transportation system. In the past, the location information of moving objects on network is collected by GPS, which cost high and has the problem of frequent update and privacy. The RFID (Radio Frequency IDentification) devices are used more and more widely to collect the location information. They are cheaper and have less update. And they interfere in the privacy less. They detect the id of the object and the time when moving object passed by the node of the network. They don't detect the objects' exact movement in side the edge, which lead to a problem of uncertainty. How to modeling and query the uncertainty of the network constrained moving objects based on RFID data becomes a research issue. In this paper, a model is proposed to describe the uncertainty of network constrained moving objects. A two level index is presented to provide efficient access to the network and the data of movement. The processing of imprecise time-slice query and spatio-temporal range query are studied in this paper. The processing includes four steps: spatial filter, spatial refinement, temporal filter and probability calculation. Finally, some experiments are done based on the simulated data. In the experiments the performance of the index is studied. The precision and recall of the result set are defined. And how the query arguments affect the precision and recall of the result set is also discussed.
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Liang Han, Kunqing Xie, Xiujun Ma, and Guojie Song "Modeling and query the uncertainty of network constrained moving objects based on RFID data", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67523Y (26 July 2007); https://doi.org/10.1117/12.761305
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KEYWORDS
Data modeling

Global Positioning System

Databases

Spatial filters

Roads

Motion models

Statistical analysis

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