Scalability and Interoperability in the Artificial Intelligence of Things

Dear Colleagues,

The rapid progress of technologies and the integration of artificial intelligence (AI) into the Internet of Things (IoT) are transforming modern communication and automation. This Special Issue delves into the key challenges and innovative solutions related to scalability and interoperability in these fields.

In this Special Issue, we focus on enhancing technologies through software and the innovative methods enabled by big data and artificial intelligence. These advancements can improve scalability, connectivity, ultra-reliable low-latency communication, and massive machine-type communication, which are crucial for supporting the increasing number of IoT devices and managing data traffic and device density.

AI enhances the functionality and efficiency of IoT systems through algorithms for pattern recognition, decision support, and predictive analytics. The convergence of AI and IoT, known as AIoT, enables smarter and more autonomous systems, driving advancements in sectors like healthcare, agriculture, and industrial automation.

Research on the scalability and interoperability of the AIoT is important for several reasons: it promotes technological innovation, boosts economic growth, and offers societal benefits by improving quality of life. This Special Issue contributes to the ongoing discussion and provides a comprehensive overview of current trends, challenges, and future directions in this rapidly evolving field.

This Special Issue aligns with the journal's scope by contributing to the ongoing discourse on advanced communication technologies and their applications. The journal focuses on big data, the Internet of Things, and artificial intelligence, which are cutting-edge research directions that could help in the advancement of the AIoT.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

• Scalable Network Architectures: Exploring innovative designs and frameworks for scalable networks to support the growing number of IoT devices.
• Interoperability Standards and Protocols: Investigating the development and implementation of standards and protocols to ensure seamless communication between diverse IoT systems and platforms.
• AI-Driven Network Optimization: Examining how AI can be leveraged to optimize network performance, manage traffic, and enhance the efficiency of networks.
• Edge Computing and AIoT: Analyzing the integration of edge computing with AIoT to improve data processing, reduce latency, and enhance real-time decision-making.
• Security and Privacy on AIoT: Addressing the challenges and solutions related to ensuring security and privacy.
• Applications of AI in IoT: Showcasing practical applications of AI in various IoT domains, such as healthcare, smart cities, industrial automation, and agriculture.
• Energy Efficiency on IoT: Investigating methods to enhance energy efficiency in networks and IoT devices to support sustainable development.
• Case Studies and Real-World Implementations: Presenting case studies and real-world implementations of scalable and interoperable AIoT solutions.
• Big Data: Exploring how AIoT technologies handle large volumes of data, including real-time data processing, tools, algorithms, and analytics techniques.
• Quality of Service (QoS): Investigating QoS mechanisms in networks to ensure high-quality data transmission, including dynamic resource allocation and QoS flow management.
• 5G and 6G: Scalability, interoperability challenges, and security and privacy in AIoT.
• Load Balancing and Scheduling: Analyzing load balancing and scheduling techniques to optimize the performance, including adaptive algorithms and network segmentation.
• Consensus: Exploring consensus methods to ensure data integrity and security, including the use of blockchain and other decentralized approaches.
• Cloud Computing: Architecture and infrastructure to support the massive scale of AIoT deployments.
• Fog Computing: Investigating how fog computing enhances efficiency and reduces latency in applications by providing data processing closer to end devices.
• Future Trends and Directions: Exploring emerging trends, future directions, and potential breakthroughs in the field.

We look forward to receiving your contributions.

Dr. Cristian González García
Guest Editor

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• AIoT
• 5G networks
• artificial intelligence (AI)
• Internet of Things (IoT)
• edge computing
• scalability
• interoperability
• network optimization