A Hybrid Indoor Localization Framework in an IoT Ecosystem

Abstract

The Global Position System (GPS) does not work in the indoor environment because of the satellite signal attenuation. To overcome this lack, we propose a Hybrid Indoor Positioning and Navigation System (HIPNS), based on Li-Fi (Light-Fidelity) localization and optical camera positioning analyses deployed in an indoor environment. The localization approach is based on the fuse of two positioning strategies where the camera-based part is responsible for localizing individuals and recovering their trajectories in zones with low coverage of Li-Fi LEDs. A third-party element is planned to operate in the event of loss of contact. So, the step detection technique and heading estimation are applied in a smartphone-based indoor localization context between two referenced points. The main contribution of this paper focuses on the use of techniques, algorithms, and methods from different spheres of application that generate heterogeneous data. We apply a data integration approach based on REST Web service architecture to allow localization operations in this hybrid indoor positioning system (HIPS). In this work-in-progress paper, we also present a state-of-the-art survey of techniques and algorithms for indoor positioning with the help of smartphones, as well as the main concepts and challenges related to this emergent area.