Wireless signal and information tracking using fuzzy logic

Eddie C.L. Chan, George Baciu, S. C. Mak

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review


Over the last decade, many commercial and government organizations as well as university campuses have deployed WLANs such as IEEE 802.11b. This has fostered a growing interest in location-based services and applications. Fuzzy logic can be applied to evaluate the behaviour of Wireless Local Area Networks (WLAN) received signal strength (RSS) and as well as to retrieve the location-aware information according to the preference of user. The behavior study of WLAN signal strength is a pivotal part of WLAN tracking analysis. Previous analytical model has not been addressed effectively for analyzing how the WLAN infrastructure affected the accuracy of tracking. In this paper, we first propose a novel fuzzy spatio-temporal topographic model. We applied the Nelder-Mead (NM) method to simplify our previous work on fuzzy color map into a topographic (line-based) map. Secondly, we propose a location-aware information retrieval application that travelers access the application with Apple's iPhones which also identify the user current location. We demonstrate our idea with 17,000 restaurants in Hong Kong and make use of fuzzy logic to return the favorable dinning place search result according to the user's preference. Our result shows that the new analytical model can provide a detail and quantitative strong representation of WLAN RSS.
Original languageEnglish
Title of host publicationComputational Intelligence
Number of pages14
Publication statusPublished - 20 Apr 2011

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X


  • Fuzzy logic
  • iPhone
  • Topographic mapping
  • Wi-Fi signal strength
  • Wireless tracking

ASJC Scopus subject areas

  • Artificial Intelligence


Dive into the research topics of 'Wireless signal and information tracking using fuzzy logic'. Together they form a unique fingerprint.

Cite this