Smartphone based Indoor Path Estimation and Localization without Human Intervention


Many different kinds of indoor positioning systems have been developed as a result of the growing market interest in services that are based on indoor localization. In spite of the extensive research that has been conducted on localization, the widespread implementation of localization is hindered by system requirements. These system requirements can take the form of a site survey, user intervention, or particular hardware or software. PYLON is a path estimation and localization system for indoor environments that we propose developing in order to overcome these limitations. PYLON is designed to operate on a smartphone and a server independently of any input from a human user. PYLON calculates an estimate of the user's path by consulting both an actual floor plan and the data collected from a widespread network of WiFi access points (APs) and Bluetooth Low Energy (BLE) beacons. It does this by generating virtual rooms based on the values of the received signal strength indicator (RSSI) and then matching those virtual rooms to actual rooms in the physical floor plan. Following the completion of the room mapping phase, PYLON employs door passing times in order to precisely refine an estimated user path. PYLON operates in a manner that is independent of the types of devices being used, in contrast to more traditional methods of path estimation and localization. We put PYLON into action on five Android smartphones and evaluate its performance with three users inside of an office building. According to the findings of our experiments, PYLON is capable of producing floor plan maps with an accuracy of 97 percent and a localization error of 1.42 meters.

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