Inverse fingerprinting: Server side indoor localization with Bluetooth low energy

Since the adoption of Bluetooth Low Energy (BLE) in the Bluetooth standard in 2010, BLE beacons are emerging as one of the most viable solutions for indoor localization due to its power efficient architecture, short scan duration, low cost chipset, and wide adoption in the devices. The existing indoor positioning systems based on BLE beacons employ the classical fingerprinting technique where user terminals collect signals from the beacons and do most of localization computations, requiring significant power consumption on user devices. However, constant power consumption on limited battery life of a mobile device can be problematic when it comes to supporting server-oriented tracking applications. In this paper, we propose and implement a new way of fingerprinting technique called inverse fingerprinting (Inv-FP), which is a server side BLE fingerprint system where most of the positioning computations are done by BLE sniffers and servers. We analyze various characteristics of Inv-FP in comparison with the classical beacon based fingerprinting system (FP), and demonstrate that Inv-FP can match the performance of FP but with minimal power consumption on user devices.