BLUNAVI: AN INDOOR POSITIONING AND NAVIGATION SYSTEM

Abstract

Indoor navigation systems have been in in- creasing demand since the introduction of
smartphone technology; however, no standard system for indoor nav- igation has been established. An indoor
navigation has many applications, for example, to help the 7.3 million visually impaired citizens in the US
to navigate indoors. Due to the weaknesses of GPS and wireless signals indoors, the problem of localizing
and tracking has proven to be difcult. Current approaches have utilized techniques such as fngerprinting
and radio frequency propagation models for localization. This paper proposes BluNavi, a cost- efcient and
widely deployable indoor navigation system. BluNavi implements and compares two modules: Wi-Fi fngerprinting and an extended Kalman Filter based on dead reckoning and bluetooth low energy beacon signals.
Each module was evaluated for its accuracy. The fngerprinting system achieved a mean accuracy of 82.33%
± 3.07% with 95% confdence. The dead reckoning model obtained a mean accuracy of 3.88m ± 0.37m
with 95% confdence. The propagation model had an accuracy of 5.91m ± 1.61m with 95% confdence. The
extended Kalman Filter with sensor fusion had an accuracy of 10.22m ± 0.91m with 95% confdence