Real- Time Spatio-Temporal Databases: Bridging the Gap Between Experimentable Digital Twins and Databases

Digital Twins (DTs) have come to be an indispensable methodology in the fields of robotics, autonomous driving, sensor simulation, Hardware-in-the-loop (HIL), Augmented reality (AR) and a variety of other fields. In this paper, we argue why databases supporting the three-dimensional (3-D) simulation of Experimentable Digital Twins (EDTs) have strict criteria, including real-time capabilities, spatial organizability of data, and temporal awareness in data representation. We thus propose the Real-Time Spatio-Temporal Database (RTSTDB) as an architecture combining these capabilities and thus meeting all EDT requirements. To facilitate real-time operation, our implementation of this concept utilizes the highly parallelized vector capabilities of Graphics processing units (GPUs). We show the successful application of our approach by providing two use cases that exhibit the identified requirements. Finally, we define a standardization for RTSTDB interfaces to maximize interoperability.