A novel method for indoor location identification

Radio Frequency Identification (RFID) is used in different applications. RFID technologies are getting considerable attention not only from academic research but also from the applications for enterprise. One of the most important applications of RFID research is the indoor position location. Many researchers have used varied technologies to perform the action of indoor position location tracking. In our research, we will propose methods using RFID tags to perform indoor position location tracking. First, we uses RFID to collect Received Signal Strength (RSS) from reference tags beforehand, and then uses multiple neuron networks models to do the indoor position location learning. Finally, when the track tags are set up in indoor environments, they can find the position of neighboring reference tags by using the neuron networks and an arithmetic mean to calculate the position location values; with this method we are able to break figures down to track tag position locations. We conducted this experiment to prove that our methodology can provide better accuracy than the LANDMARC system. We conducted the experiments to test the system accuracy.