Reconfigurable Intelligent Surface-Empowered Person Identification Using WiFi

This paper proposes a reconfigurable intelligent surface (RIS)-enhanced WiFi sensing system for respiration-based person identification (PID). By optimizing EM wave focusing, RIS improves respiration signal extraction, enabling accurate classification with a ResNet model. Experimental results achieve 92.5% PID accuracy, demonstrating the potential of RIS for wireless biometric recognition in security and smart environments.