Abstract

Using Wi-Fi signals is an attractive and reasonably affordable option to deal with the currently unsolved problem of widespread tracking in an indoor environment. These systems however suffer due to the underlying characteristics of radio waves (i.e. multipath effects) and due to infrastructural requirements. HABITS (History Aware Based Indoor Tracking System) overcomes these by modeling the historical movement habits of people in a workplace environment and then learns from these and intelligently predicts next location using a discrete Bayesian filter. This knowledge not only improves on currently available systems in terms of accuracy, yield and latency but also can be used as an input to building automation (heating, lighting) systems as an energy saving feature.