This paper proposes a new approach to solve the tracking problem for iPhones (e.g., iPhone 7) in indoor environments when Wi-Fi access point density is low. Different from the Android-based platforms, localization apps that run on iPhones are more strictly controlled by Apple. With a self localization scenario, a mobile iPhone receives signals from the Wi-Fi access points and interprets the received signals as ambient information for localizing its position in an area of interest. It also employs the inertial measurement units for navigation task. We improve the conventional pedestrian reckoning method by reducing drifting effects caused by user's walking style. Experiment results validate the effectiveness of the proposed scheme.
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Vy et al. (2019) studied this question.