An effective signal strength-based wireless location estimation system for tracking indoor mobile users

Joseph K Y NG*, Kam Yiu Lam, Quan Jia Cheng, Kevin Chin Yiu Shum

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

Localization is an essential function for location-dependent services. Although various efficient localization methods have been proposed, many of them have not tested with practical applications. Different location-dependent applications may have very different performance and operation requirements such as the accuracy in localization and frequency of location tracking. In this paper, based on our previous works on the design of efficient localization methods, we study the important issues in the design and implementation of a location tracking system for monitoring people in an indoor environment within a large building such as in rehabit centres and schools. In estimating the current location of a mobile user, we adopt the received signal strength indicator (RSSI) approach. Enhancements are proposed to improve the accuracy in localization using RSSI. To ensure the reliability of the location results and the efficiency in location tracking, it is important to minimize the traffic of location data on the network, as well as the chance of overloading the estimation system. Various issues in the design of the system are discussed and the performance results of the system are provided to illustrate the efficiency and the limitations of the proposed methods.

Original languageEnglish
Pages (from-to)1005-1016
Number of pages12
JournalJournal of Computer and System Sciences
Volume79
Issue number7
DOIs
Publication statusPublished - Nov 2013

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Applied Mathematics

User-Defined Keywords

  • Localization
  • Location estimation system
  • Location tracking
  • Ubiquitous/pervasive computing

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