A new ensemble deep learning framework for WiFi-based human activity recognition (HAR) has been developed, achieving a test accuracy of 94.87% and demonstrating strong generalization capabilities across different scenarios and hardware. This technology offers a non-intrusive and privacy-preserving alternative to traditional monitoring systems, making it suitable for smart homes and healthcare applications.