Researchers from Nanyang Technological University in Singapore have developed a new method for tracking human activity in the metaverse using WiFi signals. This approach overcomes the limitations of traditional tracking systems and significantly enhances the virtual experience by accurately and in real time tracking human movements.

WiFi sensing uses radio signals, like a radar, to detect objects and movements, including fine characteristics such as heart rate and breathing patterns. This technology expands the possibilities for creating more immersive and accurate digital environments in the metaverse.

To recognize human activity (HAR) with WiFi signals, advanced artificial intelligence (AI) models are required. The research team introduced a unique solution, MaskFi, which uses unsupervised learning to achieve high accuracy without the need for labeling large data sets.

MaskFi demonstrates nearly 97% accuracy in distinguishing human behaviors, opening the potential for transforming the metaverse by creating real-time replicas of the real world. This will significantly improve the user experience, allowing more natural interactions and movements in virtual spaces.

Beyond gaming and entertainment, WiFi sensing can change many industries by providing remote monitoring and healthcare, smart home automation, and enhanced security systems while maintaining privacy and efficiency.

The work of the scientists from Nanyang Technological University highlights the crucial role of AI in unlocking the full potential of WiFi sensing technology, bringing us closer to a fully integrated metaverse where digital and physical realities merge.