3D Visualization Indoor Positioning System with Sequence Feature Enhancement Transformer Network

Currently, Indoor Positioning Systems (IPS) deliver two-dimensional positioning information, which falls short in complex situations necessitating a three-dimensional (3D) visualization of positioning results. To address this issue, we propose an advanced 3D visualization indoor positioning system with Sequential Feature Enhancement Transformer Network (SFETNet). This system utilizes an intelligent helmet as the user's terminal collection device to gather the user's positioning information and motion information, transmitting them to the 3D visualization platform. The 3D visualization platform showcases the user's real-time position and movement status in a three-dimensional manner, providing immediate feedback. In addition, we propose the SFETNet to optimize the classification of sequential signals. SFETNet addresses the issue of limited network learning ability caused by single feature simplicity in sequential signal series, demonstrating superior accuracy and performance compared to other mainstream classification networks. This system can display the user's position and motion status in realtime with 3D visualization in complex indoor scenes. It has tremendous application potential in smart industry, healthcare, and other fields.