Submission Deadline: 31 January 2025 View: 342 Submit to Special Issue
In the context of Industry 4.0, the reliability and efficiency of industrial equipment are paramount for ensuring productivity and minimizing downtime. With the advent of artificial intelligence, significant advancements have been made in predictive maintenance and health monitoring of machinery. The integration of reliable artificial intelligence with the Industrial Internet of Things (IIoT) enables real-time monitoring and continuous health assessment of equipment. This integration ensures that industrial operations remain smooth and efficient, while also adhering to safety and regulatory standards. The primary significance of reliable AI lies in its ability to provide accurate and trustworthy insights that enhance the operational efficiency and safety of industrial processes. By leveraging advanced algorithms and machine learning techniques, reliable AI systems can predict equipment failures before they occur, thereby minimizing downtime and reducing maintenance costs.
This special issue seeks to address the challenges and opportunities in deploying reliable AI systems that are robust, safe, and trustworthy in industrial settings. We invite original research articles, review articles, and case studies that explore the advancements in reliable AI. Potential topics include, but are not limited to:
· Robust AI algorithms for fault detection and diagnosis
· Safety and reliability in AI-driven predictive maintenance
· Explainable AI for industrial health monitoring
· Case studies on reliable AI applications in industrial environments
· Real-time data processing and AI for continuous monitoring
· Advances in reliable AI models for predictive maintenance
· Resilient AI systems in the face of adversarial attacks and data noise
· Implementation of AI in industrial IoT (IIoT) environments
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