Indoor Navigation Leveraging Gradient WiFi Signals

Abstract

In this demo, we propose I-Navi, an Indoor Navigation system which leverages the gradient WiFi signal. To be more adaptive to time-variant RSSI and enrich information dimension, I-Navi exploits a three-step backward gradient binary method. Meanwhile, we adopt a lightweight online dynamic time warping (DTW) algorithm to achieve real-time navigation. We fully implemented I-Navi on smartphones and conducted extensive experiments in a five-story campus building and a newly opened two-floor shopping mall with a 90% accuracy of 2m and 3.2m achieved at two places.