AIPS: Wi-Fi Aware based Infrastructure-Free Indoor Positioning System with Fine Time Measurement
作者: Junyoung Choi, Jinwook Seo, Joohyun Lee
摘要
Indoor Positioning System (IPS) is essential for enabling location-based services in complex environments such as malls and airports. However, traditional methods struggle with cost and scalability, requiring either expensive infrastructure or labor-intensive data collection. We propose a Wi-Fi Aware-based IPS, called AIPS, a fully infrastructure-free localization system that combines Wi-Fi Aware-based peer-to-peer ranging with an inertial measurement unit, global navigation satellite system, and AI-driven indoor/outdoor detection. The system opportunistically collaborates with nearby mobile devices and leverages transaction events from mobile payment to build self-generating radio maps. To ensure the robustness of localization, AIPS adaptively switches between advanced least square and extended particle filters depending on the number of nearby mobile devices. AIPS achieves 2.62 m accuracy with a minimal battery energy cost of 0.2% per hour, offering a self-evolving and commercially viable solution for next-generation positioning.