Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions
Senthil Kumar Jagatheesaperumal, Quoc-Viet Pham, Rukhsana Ruby,, Zhaohui Yang, Chunmei Xu, and Zhaoyang Zhang

TL;DR
This paper provides a comprehensive overview of explainable AI (XAI) frameworks tailored for IoT, highlighting current applications, implementation choices, and future directions including edge XAI and 6G support.
Contribution
It offers the first holistic survey of XAI frameworks specifically designed for IoT, covering applications, implementation strategies, and future technological integrations.
Findings
XAI enhances trust in IoT applications like healthcare and smart cities.
Edge XAI structures are emerging as a key development for IoT.
6G communication supports advanced XAI deployment in IoT.
Abstract
Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines. As the number of connected devices keeps on growing, the Internet of Things (IoT) market needs to be trustworthy for the end-users. However, existing literature still lacks a systematic and comprehensive survey work on the use of XAI for IoT. To bridge this lacking, in this paper, we address the XAI frameworks with a focus on their characteristics and support for IoT. We illustrate the widely-used XAI services for IoT applications, such as security enhancement, Internet of Medical Things (IoMT), Industrial IoT (IIoT), and Internet of City Things (IoCT). We also suggest the implementation choice of XAI models over IoT systems in these applications with appropriate examples and summarize the key inferences for future works. Moreover, we…
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