Real- Time Localization of a Person Using Smart Phone

Abstract

Positioning an object has been an important topic in the recent century owing to the growth of Internet of Things (IoT). Precise localization is needed for many cases like locating people, assets management and remote healthcare. In this paper a Hybrid Location Estimation (HLE) solution is presented by combining any outdoor positioning system and PDR system using smart phone. The solution is designed to perform well in all ubiquitous environments with particular focus to urban canyon and it harnesses the strength in combining these two approaches. In addition to this a novel algorithm for Cell-id based Trilateration (CbT) is included in the proposed method. In this proposed method, the last known position or co-ordinates of the user's smart phone is first obtained followed by generating user's trajectory by Pedestrian Dead Reckoning (PDR) through the activity sequence mined using the sensors embedded in the user's smart phone. The proposed solution offers a reliable location estimation of a person in all environments. From the experimental results it is observed that the proposed HLE solution gives accuracy of 5–10 meters in the case of GPS followed with PDR and 12–17 meters in the case of CbT followed by PDR.