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Indoor Positioning Systems (IPSs) are emerging computing systems that can locate objects or people inside indoor environment. This technology shows assurance for future mobile apps that can be used in malls, museums, hospitals, airports and college campuses for self localization. Despite advances in Global Positioning System (GPS) technology, indoor spaces are still out of reach of satellites. GPS signals are not designed to penetrate most construction materials. An IPS relies on nearby anchors or landmarks, and uses various sensing schemes including artificial vision, Wi-Fi, Bluetooth, Camera images etc. In this paper, we present a system that leverages the camera and Wi-Fi present in the smart phones carried by users, to track them as they traverse in indoor environments. It makes use of a radio map of an indoor environment. A significant challenge that our system surmounts is to estimate user's position without any prior user-specific knowledge, such as the user's initial location. The results obtained after conducting simulations demonstrate the validity and suitability of the proposed algorithm to provide a high performance level in terms of positional accuracy and scalability.
Agrawal et al. (Sat,) studied this question.