Poster: Large Language Model-powered Wi-Fi-based Human Activity Recognition

Recent advances in LLMs have shown exceptional reasoning capability. However, their ability to integrate physical model knowledge for real-world signal interpretation remains largely unexplored. We introduce Wi-Chat, an LLM-powered Wi-Fi-based human activity recognition system. By embedding Wi-Fi sensing principles into prompts, we show that LLMs can infer human activities through Wi-Fi signals in a zero-shot manner without complex signal processing.