RFID enabled traceability networks: a survey
Distributed and Parallel Databases
An effective and adaptive data cleaning technique for colossal RFID data sets in healthcare
WSEAS Transactions on Information Science and Applications
A new deferred cleansing technique for effective warehousing of RFID
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Modeling sovereign RFID data streams in collaborative traceable networks
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Spatiotemporal periodical pattern mining in traffic data
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
The Journal of Supercomputing
| Hi-index | 0.00 |
Massive Radio Frequency Identification (RFID) data sets are expected to become commonplace in supply chain management systems. Warehousing and mining this data is an essential problem with great potential benefits for inventory management, object tracking, and product procurement processes. Since RFID tags can be used to identify each individual item, enormous amounts of location-tracking data are generated. With such data, object movements can be modeled by movement graphs, where nodes correspond to locations and edges record the history of item transitions between locations. In this study, we develop a movement graph model as a compact representation of RFID data sets. Since spatiotemporal as well as item information can be associated with the objects in such a model, the movement graph can be huge, complex, and multidimensional in nature. We show that such a graph can be better organized around gateway nodes, which serve as bridges connecting different regions of the movement graph. A graph-based object movement cube can be constructed by merging and collapsing nodes and edges according to an application-oriented topological structure. Moreover, we propose an efficient cubing algorithm that performs simultaneous aggregation of both spatiotemporal and item dimensions on a partitioned movement graph, guided by such a topological structure.