Resident location-recognition algorithm using a Bayesian classifier in the PIR sensor-based indoor location-aware system

  • Authors:

  • Hyun Hee Kim;Kyoung Nam Ha;Suk Lee;Kyung Chang Lee

  • Affiliations:

  • School of Mechanical Engineering, Pusan National University, Busan, Korea;School of Mechanical Engineering, Pusan National University, Busan, Korea;School of Mechanical Engineering, Pusan National University, Busan, Korea;Department of Control and Automation Engineering, Pukyong National University, Busan, Korea

  • Venue:
  • IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
  • Year:
  • 2009

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Abstract

Intelligent home service systems consist of ubiquitous sensors, a home network, and a context-aware computing system that together collect residential environment information and provide intelligent services such as controlling the environment or lighting. Determining a resident's location in the smart home or smart office is a key to such a system. This correspondence presents an enhanced location-recognition algorithm using a Bayesian classifier for the pyroelectric infrared sensor-based indoor location-aware system that is a nonterminal-based location-aware system proposed in a previous paper. This correspondence compares the conventional and enhanced location-recognition algorithms and their performance. The feasibility of the system is evaluated experimentally on a test bed.