Wireless Sensors Self-Location in an Indoor WLAN Environment

Abstract

Sometimes wireless sensors could be placed randomly without predetermined coordinates, so systems to self-locate in an area should be studied. This paper shows two approaches developed by us where wireless sensors could find their position using WLAN technology. The scenario is an indoor environment that contains walls, interferences, multipath effect, humidity and temperature variations, etc., and both approaches are based on the Received Signal Strength Indicator (RSSI). The first approach uses a training session and the position is based on Neuronal Networks using the training measurements. The second approach uses triangulation model with some fixed access points, but taking into account wall losses. In both systems we have considered the variations measured to obtain a bigger accuracy in the sensor localization.