An iBeacon Indoor Positioning System Based on Multi-Sensor Fusion

Abstract

The development of IoT and smart phone allows us to provide better guide service at public area. In this study, an indoor positioning system for guide service is proposed. For the positioning module, Particle Swarm Optimization - Growing Neural Gas (PSO-GNG) is proposed as the iBeacon positioning algorithm. Also, the idea of multi-sensor fusion is introduced. With the reliability of iBeacon positioning and Kinect positioning, this system combines the results according to data fusion with weight. Experimental results show that the proposed method can make the guide robot recognize an specific moving target from 5 people in the area with 89% accuracy.