Smartphone Based Indoor Path Estimation and Localization Without Human Intervention

The growing commercial interest in indoor localization-based services has stimulated the development of many indoor positioning systems. Despite extensive research on localization, system requirements, such as site survey, user intervention, or specific hardware/software, place limitations on the widespread deployment of localization. To overcome these limitations, we propose a path estimation and localization system for indoor environments, termed
PYLON
, that runs on a smartphone and a server without any human intervention.
PYLON
uses an actual floor plan and measurements from widely deployed WiFi access points (APs) and Bluetooth Low Energy (BLE) beacons to estimate the user’s path. It creates virtual rooms according to received signal strength indicator (RSSI) values and matches them to actual rooms in the real-world floor plan. After room mapping,
PYLON
uses door passing times to precisely refine a user’s estimated path. Unlike conventional path estimation and localization systems,
PYLON
works independently of device types. We implement
PYLON
on five Android smartphones and conduct evaluation with three users in an office building. Our experimental results show that
PYLON
achieves 97 percent floor plan mapping accuracy with a localization error of 1.42 m.