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eTwin

Customized video analytics feature extraction for next generation of digital twins in Industry 5.0: lightweight microservice-based on-the-edge model powered by bootstrap learning and deep edge technology

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NEED for AI:

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To process the data gathered from the machine and production line, and to build a virtual model that can accurately predict supply chain, production cycle, maintenance needs, and workforce management. It also helps to address the challenges of limited data availability and improve the real-world accuracy of the virtual model.

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AI REGIO SOLUTION:

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Within the eTwin experiment RGBT videos, along with advanced AI techniques, will be used to gather data and create a digital twin of the injection moulding process that can accurately predict supply chain, production cycle, maintenance, and workforce management. By using this approach, the eTwin experiment aims to overcome the challenges of limited data availability from installed sensor networks and to provide a cost-effective and accurate solution for implementing the digital twin concept.

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EXPECTED BENEFITS:

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  • Improved language skills and intercultural competences

  • Enhanced digital literacy and ICT skills

  • Increased motivation and engagement in learning

  • Strengthened European identity and sense of citizenship

The eTwin solution uses RGBT video data to overcome data availability challenges and improve the accuracy of digital twin models for injection molding processes, enabling more effective predictive maintenance and workforce management.

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