Skip to main content

Efficiently managing uncertain data in RFID sensor networks

Abstract

The ability to track and trace individual items, especially through large-scale and distributed networks, is the key to realizing many important business applications such as supply chain management, asset tracking, and counterfeit detection. Networked RFID (radio frequency identification), which uses the Internet to connect otherwise isolated RFID systems and software, is an emerging technology to support traceability applications. Despite its promising benefits, there remain many challenges to be overcome before these benefits can be realized. One significant challenge centers around dealing with uncertainty of raw RFID data. In this paper, we propose a novel framework to effectively manage the uncertainty of RFID data in large scale traceability networks. The framework consists of a global object tracking model and a local RFID data cleaning model. In particular, we propose a Markov-based model for tracking objects globally and a particle filter based approach for processing noisy, low-level RFID data locally. Our implementation validates the proposed approach and the experimental results show its effectiveness.

This is a preview of subscription content, access via your institution.

References

  1. Brusey, J., Floerkemeier, C., Harrison, M., Fletcher, M.: Reasoning about uncertainty in location identification with rfid. In: Workshop on Reasoning with Uncertainty in Robotics at IJCAI (2003)

  2. BT Research Cambridge University: Serial-level inventory tracking model. Bridge WP03. Cambridge University, BT Research (2007)

  3. Cormode, G., Garofalakis, M.: Sketching probabilistic data streams. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 281-292. ACM (2007)

  4. Dalvi, N., Suciu, D.: Management of probabilistic data: foundations and challenges. In: Proceedings of the 26th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS’07), pp. 1–12. ACM (2007)

  5. Diao, Y., Li, B., Liu, A., Peng, L., Sutton, C., Tran, T., Zink, M.: Capturing data uncertainty in high-volume stream processing. In: Proceedings of the 4th Biennial Conference on Innovative Data Systems Research (CIDR 2009) (2009)

  6. EPCGLOBAL. http://www.epcglobal.com

  7. EPCglobal EPCglobal Specifications. http://www.epcglobalinc.org/standards/specs/

  8. Fenu, G., Garau, P.: Rfid-based supply chain traceability system. In: Proceedings of the 35th Annual Conference of the IEEE Industrial Electronics Society (IECON’09), pp. 2672–2677. IEEE (2009)

  9. Fox, V., Hightower, J., Liao, L., Schulz, D.: Bayesian filtering for location estimation. IEEE Pervasive Comput. 2(3), 24–33 (2003)

    Article  Google Scholar 

  10. Franklin, M.J., Jeffery, S.R., Krishnamurthy, S., Reiss, F., Rizvi, S., Wu, E., Cooper, O., Edakkunni, A., Hong, W.: Design considerations for high fan-in systems: the hifi approach. In: Proceedings of the 2nd Biennial Conference on Innovative Data Systems Research (CIDR 2005) (2005)

  11. Garofalakis, M.N., Brown, K.P., Franklin, M.J., Hellerstein, J.M., Wang, D.Z., Michelakis, E., Tancau, L., Wu, E., Jeffery, S.R., Aipperspach, R.: Probabilistic data management for pervasive computing: The data furnace project. Bull. IEEE Comput. Soc. Tech. Comm. Data Eng 29(1), 57–63 (2006)

    Google Scholar 

  12. Gonzalez, H., Han, J., Li, X., Klabjan, D.: Warehousing and analyzing massive rfid data sets. In: Proceedings of the 22nd International Conference on Data Engineering (ICDE 2006), pp. 83–83. IEEE (2006)

  13. Ilic, A., Andersen, T., Michahelles, F.: Increasing supply-chain visibility with rule-based rfid data analysis. IEEE Internet Comput. 13(1), 31–38 (2009)

    Article  Google Scholar 

  14. Jeffery, S.R., Franklin, M.J., Garofalakis, M.: An adaptive rfid middleware for supporting metaphysical data independence. VLDB J. 17(2), 265–289 (2008)

    Article  Google Scholar 

  15. Lee, C.H., Chung, C.W.: Rfid data processing in supply chain management using a path encoding scheme. IEEE Trans. Knowl. Data Eng. 23(5), 742–758 (2011)

    Article  Google Scholar 

  16. Ma, J., Sheng, Q.Z., Ranasinghe, D.C., Chuah, J.M., Wu, Y.: A framework for distributed managing uncertain data in RFID traceability networks. In: Proceedings of the 13th International Conference on Web Information Systems Engineering (WISE 2012), pp. 298–311 (2012)

  17. Mo, J.PT., Sheng, Q.Z., Li, X., Zeadally, S.: Rfid infrastructure design: a case study of two australian rfid projects. IEEE Internet Comput. 13(1), 14–21 (2009)

    Article  Google Scholar 

  18. Nath, B., Reynolds, F., Want, R.: Rfid technology and applications. IEEE Pervasive Comput. 5(1), 22–24 (2006)

    Article  Google Scholar 

  19. Ng, B., Peshkin, L., Pfeffer, A.: Factored particles for scalable monitoring. In: Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence, pp. 370–377 (2002)

  20. Nie, Y., Cocci, R., Cao, Z., Diao, Y., Shenoy, P.: Spire: Efficient data inference and compression over rfid streams. IEEE Trans. Knowl. Data Eng., 141–155 (2012)

  21. Roussos, G., Duri, S.S., Thompson, C.W.: Rfid meets the internet. IEEE Internet Comput. 13(1), 11–13 (2009)

    Article  Google Scholar 

  22. Russell, S.J., Peter Norvig: Artificial Intelligence: A Modern Approach. Prentice Hall (2009)

  23. Sheng, Q.Z., Li, X., Zeadally, S.: Enabling next-generation rfid applications: solutions and challenges. IEEE Comput. 41(9), 21–28 (2008)

    Article  Google Scholar 

  24. Soliman, M.A., Ilyas, I.F., Chen-Chuan Chang, K.: Top-k query processing in uncertain databases. In: Proceedings of the 23rd International Conference on Data Engineering (ICDE 2007), pp. 896–905. IEEE (2007)

  25. Wang, F., Liu, P.: Temporal management of rfid data. In: Proceedings of International Conference on Very Large Databases (VLDB 2005), pp. 1128–1139. Norway (2005)

  26. Welbourne, E., Khoussainova, N., Letchner, J., Li, Y., Balazinska, M., Borriello, G., Suciu, D.: Cascadia: a system for specifying, detecting, and managing rfid events. In: Proceedings of the 6th International Conference on Mobile Systems, Applications, and Services (MobiSys 2008), pp. 281–294. New York (2008)

  27. Wu, Y., Sheng, Q.Z., Ranasinghe, D.: P2p object tracking in the internet of things. In: Proceedings of International Conference on Parallel Processing (ICPP 2011), pp. 502–511. IEEE (2011)

  28. Wu, Y., Ranasinghe, D.C., Sheng, Q.Z., Zeadally, S., Yu, J.: RFID enabled traceability networks: A survey. Distrib. Parallel Databases 29(5–6), 397–443 (2011)

    Article  Google Scholar 

  29. Wu, Y., Sheng, Q.Z., Ranasinghe, D., Yao, L.: PeerTrack: a platform for tracking and tracing objects in large-scale traceability networks. In: Proceedings of International Conference on Extending Database Technology (EDBT 2012). Berlin (2012)

  30. Zhang, Y., Lin, X., Zhu, G., Zhang, W., Lin, Q.: Efficient rank based knn query processing over uncertain data. In: Proceedings of the 26th International Conference on Data Engineering (ICDE 2010), pp. 28–39. IEEE (2010)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiangang Ma.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Ma, J., Sheng, Q.Z., Xie, D. et al. Efficiently managing uncertain data in RFID sensor networks. World Wide Web 18, 819–844 (2015). https://doi.org/10.1007/s11280-014-0283-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11280-014-0283-3

Keywords

  • RFID
  • Internet of things
  • Uncertainty
  • Traceability networks