Indoor Localization with Bluetooth Technology Using Artificial Neural Networks

Abstract

The most important function of a sensor network is to collect information from the environment. For many applications, it is important that the location or sensor that originates the collected information is ascertained. This article presents the detection of a mobile sensor's location in an indoor environment with the help of known location sensors (anchors) placed in the environment. Anchor sensors measure temperature, which is sent to a mobile phone via Bluetooth. The mobile phone can measure RSSI values of incoming signals as well as the temperature information coming from each of the anchor sensors. The Artificial Neural Network(ANN) model presented in this article was developed to detect the mobile phone location. The ANN model accepts the Received Signal Strength Indicator (RSSI) measured by the mobile phone and the anchor sensor ID number as inputs. The ANN was first trained and tested, after which the error between mobile phone locations obtained in test results and actual locations was calculated. The results were compared through the Centroid Localization (CL) method, as is known in the literature. According to the results thus obtained, it was shown that more accurate location detection was possible with the ANN model.