Abstract
This work proposes a novel concept for a semi-autonomous human-cyber-physical system (HCPS) to operate next-generation wind turbines on the way towards Industry 5.0. The exponential increase in the complexity of future wind turbines requires artificial intelligence (AI) to operate the machines efficiently and consistently. Evolving current Industry 4.0 digital twin technology beyond a sole aid for a human decision-making process, the digital twin in the proposed system is utilized for highly effective training of the AI through machine learning. Human intelligence (HI) is elevated to a supervisory level, making highlevel decisions through a human-machine interface to break the autonomy when needed. This paper points out a plausible way to realize the HCPS by identifying strategic development demands for the key enabling technologies projected from readily available knowledge.
Original language | English |
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Journal | TechRxiv |
DOIs | |
Publication status | Submitted - 2025 |
Keywords
- Wind turbine
- Human intelligence
- Artificial intelligence
- Machine learning
- Digital twin