Exploring the Synergies Between IoT, Edge Computing, Energy Management, the Metaverse, and Deep Learning for Next-Generation Intelligent Systems

Dear Colleagues,

This Special Issue is devoted to exploring the interdisciplinary convergence of the IoT, edge computing, energy management, the metaverse, and deep learning. As we enter an era where digital transformation is not just an option but a necessity, the integration of these technologies is pivotal for building intelligent systems that are both innovative and sustainable.

The importance of this topic stems from the increasing need to manage and optimize the vast amounts of data generated by interconnected devices in the IoT. Edge computing plays a crucial role here, processing data closer to their source and reducing latency, which is vital for real-time applications. Meanwhile, energy management within these systems is essential to ensure efficiency and sustainability, especially as the demand for energy grows with the proliferation of smart devices.

Deep learning, with its ability to learn from large datasets and improve over time, is key to making these systems more adaptive and intelligent. It enables predictive analytics, enhances decision-making processes, and can dramatically improve user interactions within digital environments like the metaverse—a virtual space where immersive experiences can transform everything from education to healthcare.

By highlighting the synergies between these technologies, this Special Issue aims to showcase how their combined application can lead to the development of more robust, responsive, and energy-efficient systems. This is particularly crucial in a world where environmental sustainability and efficient resource management are no longer optional but imperative for future generations.

In this Special Issue, we invite contributions that not only advance the technical aspects of these technologies but also consider their broader implications, including security, privacy, and ethical considerations. Our goal is to foster a multidisciplinary dialogue that can lead to practical solutions and innovative applications, ultimately contributing to a smarter, more sustainable future.

Submissions are invited on a variety of topics, including, but not limited to, the following:

• Architectural innovations in IoT and edge computing for enhanced energy efficiency and performance.
• Deep learning models for predictive energy management in IoT systems.
• Real-time analytics and decision making using edge computing in smart environments.
• Security and privacy challenges in integrated IoT and edge systems.
• Scalable and energy-efficient solutions for IoT and edge devices.
• Metaverse applications for sustainable energy use, including virtual simulations and training.
• AI-driven user experience and interaction design in the metaverse.
• Sustainability and resource management in the IoT and the metaverse using deep learning.
• Predictive maintenance and operational efficiency in smart cities using the IoT and deep learning.
• Ethical and social implications of deploying advanced technologies in real-world applications.
• Case studies on successful implementations of the IoT, edge computing, and energy management in various sectors.
• Interoperability and standardization in IoT and edge computing for seamless system integration.
• Emerging technologies and future trends in the integration of the IoT, edge computing, the metaverse, and deep learning.
• Challenges and opportunities in implementing deep learning in resource-constrained edge devices.
• The role of the metaverse in the remote monitoring and control of energy systems.

Dr. Tao Huang
Dr. Peng Cheng
Guest Editors

Manuscript Submission Information

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• IoT
• edge computing
• energy management
• metaverse
• deep learning
• intelligent systems