Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/82801
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Type: | Conference paper |
Title: | A framework for processing uncertain RFID data in supply chain management |
Author: | Xie, D. Sheng, Q. Ma, J. Cheng, Y. Qin, Y. Zeng, R. |
Citation: | Web Information Systems Engineering, WISE 2013, 14th International Conference, Nanjing, China, 13-15 October 2013, Proceedings, part 1/ Xuemin Lin, Yannis Manolopoulos, Divesh Srivastava, Guangyan Huang (eds.): pp.396-409 |
Publisher: | Springer |
Publisher Place: | Germany |
Issue Date: | 2013 |
Series/Report no.: | Lecture Notes in Computer Science |
ISBN: | 9783642412295 |
ISSN: | 0302-9743 1611-3349 |
Conference Name: | International Conference on Web Information Systems Engineering (14th : 2013 : Nanjing, China) |
Editor: | Lin, X. Manolopoulos, Y. Srivastava, D. Huang, G. |
Statement of Responsibility: | Dong Xie, Quan Z. Sheng, Jiangang Ma, Yun Cheng, Yongrui Qin and Rui Zeng |
Abstract: | Radio Frequency Identification (RFID) is widely used to track and trace objects in supply chain management. However, massive uncertain data produced by RFID readers are not suitable for directly use in RFID applications. Following our thorough analysis of key features of RFID objects, this paper proposes a new framework for effectively and efficiently processing uncertain RFID data, and supporting a variety of queries for tracking and tracing RFID objects. In particular, we propose an adaptive cleaning method by adjusting size of smoothing window according to various rates of uncertain data, employing different strategies to process uncertain readings, and distinguishing different types of uncertain data according to their appearing positions. We propose a comprehensive data model, which is suitable for a wide range of application scenarios. In addition, a path coding scheme is proposed to significantly compress massive data by aggregating the path sequences, the positions and the time intervals. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries. |
Description: | Lecture notes in computer science, 2013, vol. 8180 LNCS (Part 1) |
Rights: | © Springer-Verlag Berlin Heidelberg 2013 |
DOI: | 10.1007/978-3-642-41230-1_33 |
Published version: | http://dx.doi.org/10.1007/978-3-642-41230-1_33 |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
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