The Method of Location Error Detection and Correcting in Smart Home Environments

  • Authors:
  • Hyung Su Lee;Byunghun Song;Hee Yong Youn;Kwangsue Chung

  • Affiliations:
  • Sungkyunkwan University, Korea;Korea Electronics Technology Institute, Korea;Sungkyunkwan University, Korea;Kwangwoon University, Korea

  • Venue:
  • ICHIT '06 Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02
  • Year:
  • 2006

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Abstract

The location awareness system is an essential factor for the development of low cost sensor networks for use in the smart home environments and ubiquitous networking. This paper addresses the problem of tracking a moving intelligent robot using the pharos indoor location system. Our motivating applications include intelligent robot navigation, where location sensors provide position information to a moving robot. All of these applications require the position of a device moving at human speeds to be tracked. Ubiquitous indoor environments often contain substantial amounts of metal and other such reflective materials that affect the propagation of radio frequency signals in non-trivial ways, causing severe multi-path effects, dead-spots, noise, and interference. In this paper, we address the location error detection and correcting problems of the sensor network platform with RF and ultrasonic for location tracking system. Especially we present a novel detecting error of location and correcting using LQI that is particularly well suited to support context-aware smart home computing. It is achieved by considering the speed variance of the moving object and the corrected the interference errors. This proposed scheme applied the method of an error correct to the mobile object. We brought a 5% efficiencies comparing with a three existing schemes (listener inference algorithm). And The system called Pharos, aims to combine the advantages of real-time tracking systems that implement distributed environment with regardless of infrastructure or infrastructure-less wireless sensor networks.