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XR-based digital twin of Tampa built by IMERZA using Unreal Engine

IMERZA has created a world-first XR-based digital twin for Tampa’s Water Street development, leveraging Unreal Engine at its core.

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For the scale model, IMERZA used Lightact servers with Quadro RTX 6000 cards. These servers were frame-locked—synchronized on each display—using Unreal Engine’s nDisplay technology. The nDisplay system works with Unreal Engine to render 3D content simultaneously to multiple displays in real-time. The team modified the nDisplay code to allow for more granular control of passing data and to enable easier automation. Modifying the nDisplay code provided the ability to access nDisplay commands from the command-line interface, which dramatically improved the 24/7 operational requirement.

To align the digital model with the physical model, a three-point algorithm was used to get the approximate camera location in real-world space, from which IMERZA fine-tuned the position using further calculations authored in the Blueprint visual scripting system. Finally, the DCBolt team used blends and masks to fine-tune each projector for maximum visual quality.

For data that changes on a regular or real-time basis, IMERZA wrote a data aggregator that pulls from multiple sources, including commercial real-estate data sources and ESRI ArcGIS—a geographic information system for working with maps and geographic information developed by the Environmental Systems Research Institute. The aggregator normalizes the data into a new geocoded database from which the team translates the data into visuals.

“This allowed us to show all data types together in contexts, such as market data, rent growth, leasing rates over time, building data, city data, projected traffic data, real-time traffic from Google, and solar analysis,” explains Vee. “For data that changes less regularly, such as census data, we worked closely with the ESRI team to author a method to render ArcGIS map data to JPG textures, then ingest the textures at runtime.”

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