Navigating through dynamic indoor environments using WIFI for smartphones

Vinjohn V. Chirakkal, Myungchul Park, Dong Seog Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In recent days with a huge mass deployment of wireless networks, smartphones and various related services, different navigation techniques have been developed for indoor environments. Leveraging on these wireless networks, this paper proposes an indoor navigation model for a smartphone using WIFI. While a number of methods have been developed using received signal strength (RSS) based fingerprinting; only seldom approaches consider the dynamicity of the indoor environments. To tackle this limitation, we propose a positioning algorithm based on RSSI-fingerprinting and Manhattan distance which addresses navigation in a rapidly changing indoor environment. The model described is one of the efficient methods in terms of memory and battery consumption.

Original languageEnglish
Title of host publicationProceedings 2014 IEEE 4th International Conference on Consumer Electronics - Berlin, ICCE-Berlin
EditorsFrancisco J. Bellido, Dietmar Hepper, Hans L. Cycon, Alexander Huhn
PublisherIEEE Computer Society
Pages376-378
Number of pages3
EditionFebruary
ISBN (Electronic)9781479961658
DOIs
StatePublished - 5 Feb 2015
Event2014 4th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin - Berlin, Germany
Duration: 7 Sep 201410 Sep 2014

Publication series

NameIEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
NumberFebruary
Volume2015-February
ISSN (Print)2166-6814
ISSN (Electronic)2166-6822

Conference

Conference2014 4th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Country/TerritoryGermany
CityBerlin
Period7/09/1410/09/14

Keywords

  • Fingerprinting
  • Indoor localization
  • Manhattan distance
  • RSSI
  • WIFI

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