A room-level tag trajectory recognition system based on multi-antenna RFID reader

Trajectory of objects is a typical data source of indoor location aware applications and smart systems. In some object tracking applications, the continuity of moving trajectories recognition is more important than its positioning accuracy. To solve the problem of signal coverage blind areas and multi-tag identification reliability, this paper proposes a tag trajectory index method that solves the problem of localized tag trajectories between readers, and establishes a tag identification model based on RFID reader with multiple antennas, which is more economic and efficient in deployment. Furthermore, it proposes a multi-antenna optimization control scheme, which automatically adapts to the actual demands to control the number of working antennas, so as to improve the recognition efficiency. A counterpart indoor tag trajectory reasoning data structure OPTR-tree is proposed, which provides an approach for multi-tag track fast recognition in indoor environment at room-level accuracy. Both theoretical analysis and experimental results show that the proposed multi-antenna model can improve the reliability of multiple tags recognition inside buildings Hopefully, the indoor trajectories data can offer a new way for more effective disaster management.