Beacon placement algorithm for hybrid indoor positioning with Wi-Fi and bluetooth low energy

Abstract

Indoor positioning by wireless means is of significant interest in a wide range of applications; Wi-Fi and Bluetooth Low Energy (BLE) are popular candidate wireless technologies for this. We present a novel BLE beacon placement algorithm that complements existingWi-Fi infrastructure in a hybridWi-Fi/BLE positioning system. Composite signal strength measurements thus obtained, are used to derive machine learning models for location estimation. Our results show that positioning estimates at tablelevel granularity (0.9 m 1.8 m) in a computer laboratory can be achieved with 97% accuracy. This is an improvement of 20% and 30% compared to Wi-Fi and BLE only techniques respectively.