Published October 3, 2023 | Version v1
Presentation Open

A Digital Twin Framework for Field Data and Distributed Systems

  • 1. Leibniz University Hannover
  • 2. German Research Center for Artificial Intelligence
  • 3. Dresden University of Technology


Despite the considerable benefits of Digital Twins (DTs) in industry and engineering, existing DTs are primarily domain-dependent and cannot be directly generalized to more complex scenarios. This is particularly evident when the physical system corresponds to a field-dependent entity within distributed systems, which hinders a straightforward implementation of DTs by researchers. In this presentation, we discuss the fundamental concepts of a DT framework and ask how DTs can be employed for distributed systems and field-related entities. We introduce a generalized DT framework designed to encompass distributed systems across both physical and virtual spaces, with a particular emphasis on facilitating communication between these domains. Subsequently, we define the necessary components and elaborate on their specific characteristics. The functionality of these DT components in the context of digital master and digital shadows are further investigated. Furthermore, we explore a case study implemented in the GOLO archetype of the NFDI4Ing consortium. This case study involves three distinct physical entities: a vehicle equipped with the necessary tools and sensors, the public road and traffic environment, and the driver. We investigate each of these entities and show how the examined DT framework can be effectively applied.


The authors would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number 442146713.


2023_09_27_NFDI4Ing_A Digital Twin Framework for Field Data and Distributed Systems.pdf