Ferret: RFID Localization for Pervasive Multimedia

  • Xiaotao Liu
  • Mark D. Corner
  • Prashant Shenoy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4206)


The pervasive nature of multimedia recording devices enables novel pervasive multimedia applications with automatic, inexpensive, and ubiquitous identification and locationing abilities. We present the design and implementation of Ferret, a scalable system for locating nomadic objects augmented with RFID tags and displaying them to a user in real-time. We present two alternative algorithms for refining a postulation of an object’s location using a stream of noisy readings from an RFID reader: an online algorithm for real-time use on a mobile device, and an offline algorithm for use in post-processing applications. We also present methods for detecting when nomadic objects move and how to reset the algorithms to restart the refinement process. An experimental evaluation of the Ferret prototype shows that (i) Ferret can refine object locations to only 1% of the reader’s coverage region in less than 2 minutes with small error rate (2.22%); (ii) Ferret can detect nomadic objects with 100% accuracy when the nomadic distances exceed 20cm; and (iii) Ferret works with a variety of user mobility patterns.


Object Location Online Algorithm Camera Coordinate System Positive Reading Negative Reading 
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

  • Xiaotao Liu
    • 1
  • Mark D. Corner
    • 1
  • Prashant Shenoy
    • 1
  1. 1.Department of Computer ScienceUniversity of MassachusettsAmherst

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