Human localization based on inertial sensors and fingerprint in industrial internet of things ?
Localization service, especially human localization, is an indispensable component for most of technologies and applications of Industrial Internet of Things (IIoT). However, duo to the complexity of industrial environment and mobility of subjects, achieving the accurate localization solution has certain difficulty. In this paper, we propose a novel approach that leverages inertial sensors embedded in the smart phones and adopts WiFi fingerprint based on Angle of Arrival(AoA) to assist localizing, which is named as ISWF for short. Through using data from inertial sensors in smartphone and the supplementary involvement of fingerprint localization, our approach can overcome complex human movements and magnetic interferences in industrial environment. To localize users position accurately, the step length map is designed and its training process includes step boundary detection, step length estimation and orientation angle estimation. The experiments in a realistic environment validate the presented method has better localization performance in comparison to the existed methods.
human localization inertial sensor industrial internet of things wifi fingerprint