Track 10 - Artificial Intelligence for Cyber Physical Systems in Automation

Stefano Scanzio
Stefano Scanzio
CNR-IEIIT
Italy
Lukasz Wisniewski
Lukasz Wisniewski
inIT / TH-OWL
Germany

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Focus

The track is focused on theoretical formulations, technical developments, practical applications, methods and case studies that leverage Artificial Intelligence (AI), Machine Learning (ML), Data Analytics, AI/ML-based Technologies, and Emerging Technologies for the automation and optimization of Cyber-Physical Systems in smart factory settings.


Topics under this track include:

  • Self-Configuration, Self-Adaption and other Self-X for Smart Factories
  • Smart Cities, Smart Buildings and Smart Energy enhanced by AI
  • Grey-box Machine Learning
  • Real-time Implementation of AI in Automation
  • Knowledge Representation and Ontologies
  • AI-based Approaches for Security in Cyber Physical Systems
  • Unsupervised Learning and Latent Representations
  • Networked Adaptive Systems and AI-based Network Digital Twins
  • AI Powered Intelligent Interfaces to Smart Distributed Systems
  • Machine Learning and Deep Learning for Production
  • Algorithms for Predictive Maintenance, Diagnosis, and Repair
  • Explainable and Trustworthy AI in Industrial Cyber-Physical Systems
  • Industrial Conversational Agents and LLM Applications in Automation
  • Dependability of Cyber-Physical Systems
  • Data quality, Augmented and Transfer learning, Scarce data in ML
  • Time Series Prediction for Industrial Applications