Wi-Chat: Large Language Model Powered Wi-Fi Sensing

• URL: http://arxiv.org/abs/2502.12421v1
• Date: Tue, 18 Feb 2025 01:43:31 GMT
• Title: Wi-Chat: Large Language Model Powered Wi-Fi Sensing
• Authors: Haopeng Zhang, Yili Ren, Haohan Yuan, Jingzhe Zhang, Yitong Shen,
• Abstract summary: We introduce Wi-Chat, the first LLM-powered Wi-Fi-based human activity recognition system. We show that LLMs can process raw Wi-Fi signals and infer human activities by incorporating Wi-Fi sensing principles into prompts.
• Score: 3.698359226442895
• License:
• Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse tasks. However, their potential to integrate physical model knowledge for real-world signal interpretation remains largely unexplored. In this work, we introduce Wi-Chat, the first LLM-powered Wi-Fi-based human activity recognition system. We demonstrate that LLMs can process raw Wi-Fi signals and infer human activities by incorporating Wi-Fi sensing principles into prompts. Our approach leverages physical model insights to guide LLMs in interpreting Channel State Information (CSI) data without traditional signal processing techniques. Through experiments on real-world Wi-Fi datasets, we show that LLMs exhibit strong reasoning capabilities, achieving zero-shot activity recognition. These findings highlight a new paradigm for Wi-Fi sensing, expanding LLM applications beyond conventional language tasks and enhancing the accessibility of wireless sensing for real-world deployments.

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