Abstract: In the era of Internet of Things (IoT), the integration of Artificial Intelligence (AI) and IoT has become a significant trend driving technological advancements and innovative applications. With the exponential growth in the number of connected devices, enhancing end-users' trust in intelligent systems has become especially critical. Explainable Artificial Intelligence (XAI) refers to AI systems capable of providing clear explanations of their decision-making processes and outcomes. The emergence of XAI has propelled the development of AI technology and increased users' trust in AI systems. A review of the research on explainable AI in IoT applications. Firstly, the background and significance of IoT and XAI were discussed. Next, the definition and key technologies of XAI were presented. Then, the recent progress in traditional AI-driven IoT applications as well as XAI-driven IoT applications were reviewed. Furthermore, the future development directions of XAI in IoT applications were summarized and the associated challenges were discussed.

Key words: explainable artificial intelligence, deep learning, Internet of Things &#40, IoT&#41, smart healthcare

摘要： 在物联网(IoT)时代，人工智能(AI)与物联网的结合已经成为推动技术发展和应用创新的重要趋势。随着连接设备数量的指数级增长，提升终端用户对智能系统的信任度变得尤为关键。可解释人工智能(Explainable Artificial Intelligence, XAI)指能够提供其决策过程和结果解释的AI系统。XAI的出现，推动了AI技术的发展，增强了用户对AI系统的信任。对物联网应用中的可解释人工智能研究进行综述，首先介绍了IoT和XAI的相关背景及意义；进而，介绍了XAI的定义及关键技术；接着，介绍了传统AI驱动的IoT应用的最新进展和XAI驱动的IoT应用的最新进展；此外，对XAI在IoT应用中的未来发展方向和挑战进行了总结和展望。

关键词: 可解释人工智能, 深度学习, 物联网, 智慧医疗, 智慧工业, 智慧城市