Beacon Placement Algorithm for Hybrid Indoor Positioning with Wi-Fi and Bluetooth Low Energy

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 existing Wi-Fi infrastructure in a hybrid Wi-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 table-level 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.