By Topic

Location determination of mobile device for indoor WLAN application using neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Tsai, C.-Y. ; Nat. PengHu Univ. of Sci. & Technol., Penghu ; Chou, S.-Y. ; Lin, S.-W. ; Wang, W.-H.

Due to increases in the use of wireless local networks (WLANs) and mobile computing devices, and the popularity of location-based services, determining the location of a device at any time is important. Although numerous GPS-based applications have been developed and successfully utilized in various fields, they have serious limitations. Specify applicable to outdoor applications. Therefore, to develop and approach that determines the location of what that is suitable for indoor environments is necessary. This study presents a novel location determination mechanism that uses an indoor WLAN and back-propagation neural network (BPN). A museum is taken as an example indoor environment. Location determination is achieved using the combined strengths of 802.11b wireless access signals. With a significant numerous access points (APs) installed in the museum, hand-held devices can sense the strengths of the signals from all access points to which the devices can connect. Using a back-propagation network, device locations can be estimated with sufficient accuracy. A novel adaptive algorithm is implemented.

Published in:

Intelligent Environments, 2008 IET 4th International Conference on

Date of Conference:

21-22 July 2008