  Digital twins are becoming increasingly popular across many industries for
real-time data streaming, processing, and visualization. They allow
stakeholders to monitor, diagnose, and optimize assets. Emerging technologies
used for immersive visualization, such as virtual reality, open many new
possibilities for intuitive access and monitoring of remote assets through
digital twins. This is specifically relevant for floating wind farms, where
access is often limited. However, the integration of data from multiple sources
and access through different devices including virtual reality headsets can be
challenging. In this work, a data integration framework for static and
real-time data from various sources on the assets and their environment is
presented that allows collecting and processing of data in Python and deploying
the data in real-time through Unity on different devices, including virtual
reality headsets. The integration of data from terrain, weather, and asset
geometry is explained in detail. A real-time data stream from the asset to the
clients is implemented and reviewed, and instructions are given on the code
required to connect Python scripts to any Unity application across devices. The
data integration framework is implemented for a digital twin of a floating wind
turbine and an onshore wind farm, and the potential for future research is
discussed.
