Front End to Back End Speech Scrambler

Abstract

As modern mobile devices are often equipped with a WLAN interface and many buildings are equipped with a WLAN infrastructure, WLAN could be used for localization. The aim of this work is to investigate the quality of different indoor positioning methods based on values of WLAN received signal strength index (RSSI) using commercially available devices (smart phones, personal digital assistants). Three positioning algorithms were considered: minimal Euclidian distance, intersections of RSSI-Isolines and a stochastic model based on Bayes' theorem. A measuring test bed within an empty seminar room, four different types of personal digital assistants (Dell, Fujitsu, HP, T-Mobile) and two types of access points (Netgear, Lancom) were used. No modification of hardware and software was conducted. Furthermore this paper shows how WLAN localization can be applied in a museum guide application. This paper also shows the visualization of spatial user position frequency pattern during a field trial within a museum.