Evaluating Indoor Location Triangulation Using Wi-Fi Signals

Abstract

The advancement in Global Positioning System (GPS), has led to a huge number of location-based applications. Such applications can also be very useful for indoor environment; however, GPS technology struggles with indoor location mapping. Currently, there are various techniques, which are used for indoor localization namely: wireless fidelity-based, Bluetooth, radio frequency identification (RFID), infrared beam, and Sensors. The Wi-Fi access points (APs) are installed at various indoor locations to cover most of the areas, and the smart phones and tablets, are equipped with wireless transceiver modules, which can receive Wi-Fi signals. Therefore, it becomes more practical to use Wi-Fi signal for such application in comparison to infrared beam, Bluetooth and other wireless technologies, as Wi-Fi has significant advantages, including wider range, higher stability, and there are no requirements for additional hardware devices. Literature review confirms that the non-line of sight (NLOS) factors and the multipath effect easily affects most of the existing indoor localization algorithms based on Wi-Fi access points (APs). There also exist many other problems, such as positioning stability and blind spots, which can cause a decline in positioning accuracy at certain positions or even failure of positioning. In this research, we propose to use triangulation of location based on Wi-Fi signals from multiple APs. This method utilizes the received signal strength indications (RSSI) from multiple static APs to determine the location. Based on this, evaluation is done using experiments to measure the accuracy and effectiveness of the new proposed algorithm. The results are promising and can be improved with the use of Artificial intelligence, which is the future work of this project. The proposed method will overcome most of the problems caused by NLOS factors and the multipath effect.