Dear Colleagues,

The intelligent Internet of Things (IoT) and cyber–physical systems (CPS) are evolving quickly as interdisciplinary technologies that combine physical components and computational devices to enable artificial intelligence (AI)-based solutions. These solutions are characterized by a deep, complex intertwining process between cyber components, sensors, and intelligent technologies (such as machine learning and deep learning) for communication, computation, and control that involve edge computing, as well as dynamic physical components that include mechanical components, human activities, and the surrounding environment.

Intelligent automotive and transportation systems, smart agriculture, intelligent avionics systems, smart homes, smart grids, smart healthcare systems, intelligent wearable systems, intelligent energy systems, robotic systems, and so on are all examples of intelligent IoT and CPSs. Introducing edge/fog computing and machine/deep learning-based intelligence approaches to IoT and CPSs can boost performance in a variety of ways. Despite the potential benefits, a number of challenges arise, such as a lack of agreement on any reference models or best practices, security and privacy concerns, and new modelling and networking challenges arising from the intrinsic complexity of computation, communication, and control with physical systems, among others.

This Special Issue (SI) intends to draw academic and industrial researchers' attention to fundamental issues in intelligent IoT and CPS from a variety of viewpoints, including architectures, algorithms, energy conservation, and applications. Technical directions for research include fog/edge/cloud computing; intelligent computation and communication; and smart infrastructure deployment, among others, to contribute to the development of sustainable IoT and CPS services. The list of possible topics includes, but is not limited to:

• Novel theories, concepts, and paradigms on the convergence of AI, edge–cloud, and IoT/CPS;
• Innovative learning models for intelligent IoT and CPS applications;
• System architectures for intelligent IoT systems and CPS;
• Collaborative learning frameworks toward the cloud–edge-end continuum;
• Security and privacy of edge/cloud computing-based learning models;
• Future-based CPS, including their experimental evaluation;
• Energy efficient operations and optimization;
• Real-time intelligent IoT applications/CPS;
• Novel collaborative frameworks/algorithms/protocols for intelligent IoT applications;
• Ultra-reliable and low latency communication protocols for intelligent IoT applications;
• Collaborative resource management frameworks and task scheduling algorithms for the cloud–edge-end continuum;
• Smart threat models and risk management for intelligent IoT applications/CPS;
• Federated learning and distributed learning for large scale IoT/CPS;
• artificial intelligence enabled distributed edge computing for the Internet of Things;

Innovative applications in intelligent IoT systems such as in the area of intelligent automotive and transportation systems, smart logistics, smart agriculture, smart healthcare, smart grids, and industry 4.0.

Dr. Mike Oluwatayo Ojo
Dr. Billy Kihei
Dr. Augustine Ikpehai
Guest Editors

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• intelligent internet of things
• cyber–physical systems
• edge intelligence
• smart systems
• deep learning
• edge computing
• distributed learning
• federated learning
• machine learning
• intelligence iystems
• artificial intelligence
• cognitive communication and networking
• cloud computing/edge computing
• privacy and security