Floor Number Detection for Smartphone-based Pedestrian Dead Reckoning Applications

Abstract

We present a new floor number detection algorithm for use in smartphone-based indoor localisation systems. It is designed to complement any pedestrian dead reckoning (PDR) algorithm able to detect steps and estimate a 2D trajectory from data of the smartphone's inertial measurement unit.

Our proposed method is based on the Viterbi algorithm, fusing data from an off-the-shelf smartphone's accelerometer, barometer and wifi received signal strength (RSS) measurements. The accelerometer is used to detect accelerating elevators, while the barometer is used to detect stair climbing. This is combined with model-based wifi RSS fingerprinting, enabling accurate floor number detection. Our system is tested in an office environment with 7 41 m x 27 m floors, each of which has 2 pre-existing wifi access points. The algorithm is evaluated with a total of 116 minutes of recorded data, in which the floor number changed 76 times and a distance of 4.8 km was travelled. Since the Viterbi algorithm allows to easily correct past states (i.e. floor numbers) based on new information, it is evaluated in real-time and batch mode. Our proposed algorithm achieves a floor number detection accuracy of 99.1% (real-time) and 99.7% (batch), while using only RSS measurements resulted in 91% accuracy.