Internet of Things (IoT) applications have permeated a broad range of aspects of human life as a result of advances in semiconductor technology. Many new technologies also facilitate this general use, including artificial intelligence (AI) and blockchain. The rapid advancement of AI technologies, such as deep learning, represents an exciting opportunity to extract reliable information from large amounts of raw sensor data in IoT applications. Blockchain is gaining traction in the development of IoT applications to address security and privacy concerns due to its immutability and distributed nature. AI and blockchain have developed into game-changing technologies for accelerating the development of IoT ecosystems with tremendous growth, impact, and promise. Sustainable computing, which provides an environment conducive to energy conservation, is critical for energy-constrained IoT devices. However, AI and blockchain were not designed for this kind of IoT environment. Both methods are computationally intensive and can create significant bandwidth overhead and latency. These stringent performance and power requirements are incompatible with the majority of IoT devices. Although new computing paradigms such as edge computing have been developed to offload computation-intensive activities off low-power IoT devices, many operations must still be performed on IoT devices for security and privacy reasons (i.e., keep data locally). Recent years have seen an increased interest in research on novel computer architectures, lightweight deep learning, and blockchain technologies. The use of lightweight deep learning models with blockchain-based architectures can ensure the long-term viability of the IoT. This Special Issue will include the latest advances and research findings on sustainable computing for upcoming IoT applications driven by AI and blockchain. It intends to offer a forum for academics and practitioners from all over the world to develop innovative solutions to current problems. The topics of interest include, but are not limited to:

- Lightweight deep learning models with blockchain-based architectures for IoT.
- Fusion of artificial intelligence and blockchain for sustainable IoT.
- Intelligence for sustainable computing in emerging IoT applications.
- Blockchain-based AI models for sustainable computing in emerging IoT applications.
- Sustainable IoT networks supported by AI: privacy and accountability.
- New computing architectures for sustainable IoT systems.
- Theoretical considerations for AI and blockchain-enabled sustainable IoT designs.
- Energy-efficient communication protocols for IoT systems driven by AI and blockchain.
- Security and privacy issues in sustainable computing for IoT applications.
- Energy-efficient communication protocols for IoT systems driven by AI and blockchain.
- Case studies in sustainable computing for IoT applications powered by AI and blockchain.