AI and Optimization in Industrial Networks: Advancing Efficiency, Real-Time Decisions, and Security
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".
Deadline for manuscript submissions: 31 August 2025 | Viewed by 504
Special Issue Editors
Interests: vehicular communications; cyber-physical security
Special Issue Information
Dear Colleagues,
AI-powered algorithms are increasingly enhancing industrial networks, machine vision, robotics control, and large-scale industrial models, boosting operational efficiency, real-time decision making, and safety. However, in complex industrial internet environments, challenges such as cross-layer communication optimization, computing–networking cross-domain resource allocation, and task scheduling are deeply intertwined, complicating integrated intelligent decision making. Additionally, the highly dynamic nature of industrial environments and network topologies, along with the stringent demands for stability and rapid response, impose significant challenges on the reliability and security of data-driven decision-making models. Addressing these obstacles is essential for advancing system optimization, predictive maintenance, intelligent control, and industrial cybersecurity.
This Special Issue invites original research papers, short communications, and review articles focused on the integration of optimization and machine learning techniques in industrial environments. The aim is to explore how these technologies can accelerate industrial transformation, improve real-time decision making, and ensure robust and reliable operations in complex, dynamic settings. The topics of interest include the following:
- Wireless-Enabled Industrial Networks: Optimization of wireless protocols and architectures for high-reliability, low-latency communication in industrial environments, including Industrial IoT (IIoT) and time-sensitive networking (TSN).
- AI-Driven Robotics Control: Machine learning techniques for the autonomous and adaptive control of industrial robots, including collaborative robots (cobots) and autonomous mobile robots (AMRs), in complex, dynamic environments.
- Industrial Vision Systems: Advanced AI methods for real-time defect detection, quality assurance, and object recognition in smart factories, leveraging edge computing and 5G/6G connectivity for real-time processing.
- Large Industrial AI Models: Development and application of large-scale AI models tailored to industrial tasks, including predictive analytics, process optimization, and cross-domain learning, facilitated by next-gen communication systems.
- Industrial Security and Privacy: The scale and complexity of big data heighten privacy risks, expand the attack surface, and increase cyber threats, jeopardizing data integrity.
Dr. Kun Hua
Dr. Hansong Xu
Guest Editors
Manuscript Submission Information
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Keywords
- wireless communication for IIoT
- edge AI
- distributed learning
- 5G/6G robotics
- safety algorithms
- cyber–physical systems
- digital twins
- security
- privacy
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