A Probabilistic Room Location Service for Wireless Networked Environments

  • Paul Castro
  • Patrick Chiu
  • Ted Kremenek
  • Richard Muntz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2201)


The popularity of wireless networks has increased in recent years and is becoming a common addition to LANs. In this paper we investigate a novel use for a wireless network based on the IEEE 802.11 standard: inferring the location of a wireless client from signal quality measures. Similar work has been limited to prototype systems that rely on nearest-neighbor techniques to infer location. In this paper, we describe Nibble, a Wi-Fi location service that uses Bayesian networks to infer the location of a device. We explain the general theory behind the system and how to use the system, along with describing our experiences at a university campus building and at a research lab. We also discuss how probabilistic modeling can be applied to a diverse range of applications that use sensor data.


Bayesian Network Access Point Location Service Quality Setting Conference Room 
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 2001

Authors and Affiliations

  • Paul Castro
    • 1
  • Patrick Chiu
    • 2
  • Ted Kremenek
    • 1
  • Richard Muntz
    • 1
  1. 1.Department of Computer ScienceUCLALos AngelesUSA
  2. 2.FX Palo Alto LaboratoryPalo AltoUSA

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