RollCaller: User-friendly indoor navigation system using human-item spatial relation

Indoor navigation has received much attention in academics and industry in recent years. Previous methods often attempt to locate users with various localization algorithms in combination with an indoor map, so they need expensive infrastructures deployed in advance. In this study, we propose to utilize existing indoor objects attached RFID tags and the reader to navigate the user to the destination, without need of any extra hardware. The key insight is that the personal movement takes an impact on the Doppler frequency shift values collected from the indoor objects when getting close to the tag. Such local human-item spatial relation is leveraged to infer the users position and further navigate user to destination step by step. We implement a prototype navigation system, called RollCaller, and conduct comprehensive experiments to examine its performance.