Design of An Indoor Positioning Scheme Using Artificial Intelligence Algorithms

An intelligent positioning approach based on artificial intelligence algorithms has been introduced in an indoor environment for precise positioning and decision making through adaptation and learning. Firstly, distances between the reference and randomly generated nodes are being identified using a predefined sphere. These references nodes are adapted as input points in back-propagation algorithm of neural network in that domain space. To achieve precise positioning and better decision making, the information from neural network outputs is used in a fuzzy controller which acts as the second model of the proposed system. The rule sets of fuzzy controller can enhance the performance of the system. The effectiveness of the proposed algorithm has been tested through simulation results where MATLAB neuro-fuzzy logic toolbox app is used for simulation purposes.