Insufficient data volume and quality are particularly pressing challenges in the adoption of
modern subsymbolic AI. To alleviate these challenges, AI simulation recommends …

The dramatic recent increase of the smart Internet of Everything (IoE) in Industry 4.0 has
significantly increased energy consumption, carbon emissions, and global warming. IoE …

Traditional make-use-dispose operations are no longer an option in the manufacturing
sector–companies face mounting sustainability pressures and incentives to move towards …

Cyber–physical systems are developed to meet the need to improve process flexibility,
optimality, and transparency through Digital Twin (DT). Unfortunately, the application of DT …

The concept of digital twins has been in the field for a long time, constantly challenging the
specification, modeling, design, implementation, and exploitation of complex cyber–physical …

The next generation of engineered systems ought to be more sustainable. In this context,
Digital Twins play a crucial role as key enablers of sustainability ambitions in systems …

Road infrastructure is facing significant digitalization challenges within the context of new
infrastructure construction in China and worldwide. Among the advanced digital …

Digital twins are gaining relevance in many domains to improve the operation and
maintenance of complex systems. Despite their importance, most efforts are currently …

Digital twins (DTs) encapsulate the concept of a real-world entity (RE) and corresponding
bidirectionally connected virtual one (VE) mimicking certain aspects of the former in order to …

Insufficient data volume and quality are particularly pressing challenges in the adoption of
modern subsymbolic AI. To alleviate these challenges, AI simulation recommends …