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A Framework for Distributed Managing Uncertain Data in RFID Traceability Networks

  • Jiangang Ma
  • Quan Z. Sheng
  • Damith Ranasinghe
  • Jen Min Chuah
  • Yanbo Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7651)

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 remains 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.

Keywords

RFID Internet of Things Uncertainty Traceability Networks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jiangang Ma
    • 1
  • Quan Z. Sheng
    • 1
  • Damith Ranasinghe
    • 1
  • Jen Min Chuah
    • 1
  • Yanbo Wu
    • 2
  1. 1.School of Computer ScienceThe University of AdelaideAustralia
  2. 2.Beijing Jiaotong UniveresityBeijingChina

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