OpenTwins: an open-source framework for the development of next-gen compositional digital twins

Abstract

Although digital twins have recently emerged as a clear alternative for reliable asset representations, most of the solutions and tools available for the development of digital twins are tailored to specific environments. In this paper, we present an open-source framework for the development of compositional digital twins, i.e., digital twins that can be composed of other digital twins. In this open framework, digital twins can be easily developed and orchestrated with 3D-connected visualizations, IoT data streams, and real-time machine-learning predictions.