Explainable AI and Internet of Things Convergence: Applications, Security, Trends and Industry Cases

Internet of Things (IoT) and Explainable Artificial Intelligence (XAI) have dominated the research landscape recently. The IoT growth is attributed to the continuous need to achieve a connected world made possible by the development in communication capability of computing-centric devices. XAI on the other hand have attracted research and global attention due the desire for trustworthiness, interpretative and auditable AI decisions and the need to account for the role of AI in human activities. It is noteworthy that the convergence of XAI and IoT will usher in exciting opportunities and challenges across various domains including healthcare, smart cities, manufacturing, transportation, agriculture and beyond. However, there have been documented challenges of IoT applications such as battery limitation, energy harvesting, sensor placement, intrusion detection, etc. Attempts at the use of AI to curb these challenges have yielded appreciable results. But will XAI change the paradigm? Offering better possibilities and pushing the research boundaries? Moreover, XAI researchers and engineers are faced with the dilemma of how best to select the most appropriate XAI tools and applications and how to compensate for the unique IoT requirements in embedding the XAI models. This is in addition to the need for Tiny XAI models in cases where the latency, and computational complexities is critical. Current challenges of adopting XAI to IoT cases include the complexity of IoT data, requiring interpretative models that can handle heterogeneous data sources, resource-constrained IoT devices, privacy and security issues and the need to ensure transparency and trustworthiness in XAI models. In the future, IoT will leverage 6G guaranteeing massive-scale deployments, and supporting smart cities with advanced infrastructure management ad environmental monitoring. This Topical Collection aims to highlight the latest advancements, methodologies, and applications in this interdisciplinary area. As the guest editors, we welcome research, reviews, working papers, and industry cases to the address issues in the XAI and IoT convergence.

Topics of interest include but not limited to:

• Explainable AI techniques for IoT data Analysis and decision making

• Interpretable machine learning models for IoT systems

• Trust, fairness, and accountability in AI-driven IoT environments

• Applications of XAI in IoT-enabled smart environments

• Security challenges and solutions in XAI and IoT convergence

• Industry use cases, success stories, reviews and best practices

We welcome submissions that present novel research findings, practical implementations, and theoretical insights related to XAI and IoT convergence. All submissions will undergo rigorous peer review process, to ensure high quality and relevance to the themes of the Topical Collection.

Keywords: Explainable AI; Intrusion Detection; Artificial Internet of Things (AIoT); Smart environments; Generative AI; Digital Twin; Machine Learning; Smart Agriculture; Smart Factory and Manufacturing; Smart Home; Smart City