• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.71-78
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• 2014

The RFID-tag objects can be recognized by a distinct reader where it is installed. The RFID-tag objects are likely described as storages rather than the mobiles in the use of GPS. As RFID tags are large in number compared to moving objects, so the storing and retrieval costs are highly expensive. Here, two solutions for spatio-temporal model taking account of the feature in the tagged objects are proposed. First, the moving-tag objects are expressed by the terms "now" as well as "path location". Second, the size of storing index was noticeably reduced by not saving the tag information of palletizing products but mapping the tagged objects.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.65-75
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• 2005

Moving-objects databases should efficiently support database queries that refer to the trajectories and positions of continuously moving objects. To improve the performance of these queries. an efficient indexing scheme for continuously moving objects is required. To my knowledge, range queries on current positions cannot be handled by the 3D R-tree and the TB-tree. In order to handle range queries on current and past positions. I modified the original 3D R-tree to keep the now tags. Most of spatio-temporal index structures suffer from the fact that they cannot efficiently process range queries past positions of moving objects. To address this issue. we propose an access method, called the Tagged Adaptive 3DR-tree (or just TA3DR-tree), which is based on the original 3D R-tree method. The results of our extensive experiments show that the Tagged Adaptive 3DR-tree outperforms the original 3D R-tree and the TB-tree typically by a big margin.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1250-1256
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• 2004

The movement of continuously changing positions should be stored and indexed for querying current and past positions. A simple extension of the original R-tree to add time as another dimension, called 3D R-tree, does not handle current position queries and does not address the problem of low space utilization due to high overlap of index nodes. In this paper, 1 propose the dynamic splitting policy for improving the 3D R-tree in order to improve space utilization of split nodes. 1 also extend the original 3D R-tree by introducing a new tagged index structure for being able to query the current and past positions of moving objects. 1 found out that my extension of the original R-tree, called the tagged dynamic 3DR-tree, outperforms both the 3D R-tree and 75-tree when querying current and past position.