The integration of Internet of Things (IoT), big data, and artificial intelligence (AI) has paved the way for a number of novel real-world applications. These converged technologies cover not only information and communication technology, but also interconnect various industries such as businesses, industrial automation, smart farming, and healthcare, among others. IoT connects the physical world to the Internet and generates huge volumes of big data that needs to be refined to extract useful features using machine learning (ML) and deep learning (DL).

There are numerous challenges of underutilizing the big data generated by IoT devices from the ML/DL and AI perspective. It is argued that AI is mandatory for big data analytics to deal with these challenges. A learning framework is required to match the nature of data produced in the IoT environment, which needs to be scalable enough to fulfill the requirements of the services demanded by smart IoT applications. As the data is collected on a massive scale in IoT, and the data analytics is gradually becoming mature, it is possible to conquer such challenges with novel AI algorithms and ML/DL techniques to analyze in real-time.

This Special Issue is open to original research and review articles exploring the role of AI, ML/DL, big data, and IoT in multidisciplinary domains. This includes the analysis, modeling, simulation, and applications of these cutting-edge technologies. Contributions on frameworks and architectures of IoT integrated with AI, ML/DL, and big data with their emerging applications are also encouraged. Contributions describing the applications of these technologies in alleviating natural disasters, pandemic diseases, ensuring road safety, and mitigating environmental pollution are welcome.

Potential topics include but are not limited to the following:

• IoT-enabled architectures and system designs for big data analysis
• Big data systems modelling, analysis, and simulation in IoT applications
• ML/DL and AI-based systems analysis, modelling, and simulation in IoT applications
• Design and implementation of security in IoT-based applications
• IoT-enabled big data analytics using ML/DL and deep learning algorithms
• ML/DL interplay for smart and intelligent applications of IoT
• Big data analytics and ML/DL for IoT security
• Applications of IoT, AI, and big data in education
• Applications of IoT, AI, ML/DL, and big data in physical education and sports
• Novel and sustainable IoT architectures based on big data analytic
• Trust, privacy, and security of ML/DL techniques for smart IoT applications