# Geo-Spatial Context Provision for Digital Twin Generation
## 3 A Digital Twin Architecture Linking CPS Behavior and Produced Operational Data
### Exemplifying Use Case Scenarios  
As outlined in the previous section, process model execution information is integrated with the (geo-spatial) context provided by the system at certain relevant points of the process. This supports the tracking of the logistics process and makes the system observable  
Figure 10: Generic steps for realizing the proposed digital twin architecture.  
for the stakeholders. Figure 11 illustrates this for the communication between the robot and the transport box upon successfully completing the outfitting of the box.  
Different cross-cutting concerns with regard to the processes, the system, and the environment can be assessed by stakeholders. This goes beyond the monitoring of standard behavior. Considering the outlined vaccine use case, it would be possible to show the structural integrity of vaccine packaging (by, e.g., recognizing surface deformities) at different points in the process, to help rule out that damage occurred during transport preparation. The two following examples should help illustrate other possible applications of the proposed twin:  
* **Digital Process Twin Application Example 1:** After the successful transportation of a box to its destination, the organization in charge of transport preparation receives the complaint that a sensor was not installed that should have been installed. The person in charge of supervising the process accesses past process model instances and looks at the one of the package in question. Both the model execution history and the scan results associated with states show that the sensor in question was installed properly, showcasing that it went missing after the package left the care of the organization. The behavioral twin of the box itself (enriched with the produced sensor readings) shows that it was operating as intended during the transport process as well, indicating that the sensor was probably removed at a later point in the process.
* **Digital Process Twin Application Example 2:** The person in charge of supervising the transport preparation process receives a notification on their smartphone from the robot that it cannot continue with its normal behavior due to unexpected changes in the environment that it cannot compensate for. The supervisor looks at the process  
Figure 11: An example for the monitoring of the standard behavior of components and the related data. Data that concerns both a send state and a receive state was associated with the message connecting the two.  
model instance that is being executed and sees that the robot is currently in the process of selecting a sensor for installation. Upon accessing and viewing the scan data associated with the current point in the process, it can be seen that the shelf was moved and sensors had fallen to the ground due to a minor earthquake or some other disturbance. Subsequently, the supervisor can react and restore the original environment based on what is known about the set-up (both a priori and from earlier scans as part of the process).  
Instead of having to view the environmental data as a time-series of scan data without additional context, stakeholders can use the created process model instances (and the past model instance documentations stored) to immediately access the points in the process that they are interested in. The saved data can be used for both manual and automated analysis to gain insights regarding the CPS-supported business process and the CPS itself. These aspects of the proposed digital twin of the CPS are akin to process monitoring and auditing, as it is enabled through workflow execution engines in the context of business process management (the field from which subject-oriented modeling originates). Furthermore, considering the proposed DT model, one can opt to only create \"snapshots\" of the operational environment at crucial states in the process and store them, instead of continuously saving point clouds throughout the whole operation of the system, to minimize the data that needs to be stored.