A Robust Location Tracking Using Ubiquitous RFID Wireless Network

  • Keunho Yun
  • Seokwon Choi
  • Daijin Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4159)


A dangerous workplace like the iron production company needs a durable monitoring of workers to protect them from an critical accident. This paper concerns about a robust and accurate location tracking method using ubiquitous RFID wireless network. The sensed RSSI signals obtained from the RFID readers are very unstable in the complicated and propagation-hazard workplace like the iron production company. So, the existing particle filter can not provide a satisfactory location tracking performance. To overcome this limitation, we propose a double layered particle filter, where the lower layer classifies the block in which the tag is contained by the SVM classifier and the upper layer estimates the accurate location of tag owner by the particle filter within the classified block. This layered structure improves the location estimation and tracking performance because the evidence about the location from the lower layer makes a effective restrict on the range of possible locations of the upper layer. We implement the proposed location estimation and tracking system using the ubiquitous RFID wireless network in a noisy and complicated workplace (100m × 50m) where which 49 RFID readers and 9 gateways are located in the fixed locations and the maximally 100 workers owning active RFID tags are moving around the workplace. Many extensive experiments show that the proposed location estimation and tracking system is working well in a real-time and the position error is about 2m at maximum.


Particle Filter Location Estimation Location Tracking Restricted Time Majority Vote Scheme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Keunho Yun
    • 1
  • Seokwon Choi
    • 1
  • Daijin Kim
    • 1
  1. 1.Department of Computer EngineeringPOSTECHKorea

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