An indoor location identification system based on neural network and genetic algorithm

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 neuro networks models to do the indoor position location learning. Next, genetic algorithm is used to find the weight of each neural network. Finally, when the track tags are set up in indoor environments, they can find the position of neighboring reference tags by using the neuro 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 single neural network. We conducted this experiments to test the system performance and accuracy.