SensingAgents: A Multi-Agent Collaborative Framework for Robust IMU Activity Recognition

The article introduces SensingAgents, a novel multi-agent collaborative framework designed to enhance Human Activity Recognition (HAR) using Inertial Measurement Unit (IMU) sensors. By leveraging Large Language Models (LLMs), SensingAgents organizes specialized roles among agents to address challenges such as reliance on labeled data and position-specific ambiguities in current HAR models. This innovative approach aims to improve the robustness and transparency of activity recognition systems.