Nowadays, to meet the demands of Industry 4.0, a seamless convergence between the different cloud domains (edge, edge and cloud) is key for industries to have a cloud-native intelligent orchestration layer capable of establishing the necessary mechanisms to ensure continuity of services as data m

In industrial environments, cloud services and the Internet of Things (IoT) converge, with the need to manage complex and diverse computing environments for service and infrastructure providers, a process called cloud continuum.

Data scientists spend much time with data cleaning tasks, and this is especially important when dealing with data gathered from sensors, as finding failures is not unusual (there is an abundance of research on anomaly detection in sensor data).

In the field of plant disease protection, many approaches exist, but all acknowledge the necessity of fast and accurate identification of the source in order to make the most efficient applications.

In general, one of the complexities of large simulations is related to the usage of the heterogeneous computational resources that are needed to execute them. The definition of workflows, usually linked to concrete orchestrations solutions, has reduced most of that complexity.

Accurate digital twinning of the global challenges (GC) leads to computationally expensive coupled simulations.