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Artificial intelligence (AI), quantum computing and the metaverse are now a part of the human lexicon, leading some scientists and philosophers to believe simulation theory is a possibility. Simulation theory is the idea that everything around us is a simulation by a higher power – a modern take on Plato's "Allegory of the Cave" from his work Republic published in 375 BC.   

If you disregard the world simulation theory as a singular concept and focus on the amalgamation of multiple simulations, physical to digital cloning of worldly objects, and the use of golden record data, the novel but abstract idea of a digital creatio ex nihilo (creation out of nothing) exists. The ability to start with nothing and construct these digital new worlds, create new bonds between the digital and physical, and develop new, exciting, unforeseen interactions has become a reality.    

The Digital Twin started at NASA in the 1960s in response to Apollo 13's oxygen tank explosion and subsequent damage to the main engine. Since then, 60 years of technological advancements across GPUs, scene graphs, ray tracing, edge computing, 5G, Quantum, AI/ML, autonomous systems, 3D modeling software and IoT have led to the ability to mirror physical environments in the digital realm. In this whitepaper, I'll expand the current definition of Digital Twins and how they will transform into a true metaverse.   

Key definitions

Digital Twin (DT): A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object and/or process (individual DT). Two ideal states make up the paradigm of a DT. The individualistic DT harmoniously consumes and creates data bidirectionally by conserving its functional condition while potentially interacting within the holism of a larger ubiquitous DT. 

Digital Metamorphosis: The creation ("the beginning") of a Digital Twin transforming through phases into an established multi-user digital utopia ("the verse"). 

Digital "Verse" (Metaverse): The utopian model is the digital replication of the physical world (DT) into a human, interactive, digital, metaphysical realm. 

Creation of a city-scale digital twin

The construction of a city-scale digital twin recently became cost-effective, data-realistic and computationally possible for Industry 4.0, enterprises, federal and other government agencies in the last few years. Existing cities, as opposed to new construction, can be developed as high-fidelity twins used for many purposes, including: 

  • Intelligent disaster preparedness and response
  • Traffic planning and modeling
  • Road construction and traffic mitigation
  • City design, cellular placement, lighting and smart cameras
  • New facility construction, including the integration of REVIT (time-lapse)

Similar to the complexities of cities, large enterprises, higher education and federal campuses can utilize the above benefits and additional capabilities within a high-fidelity twin.  These include: 

  • Utilizing the campus as a training range for:
    • Complex multi-team simultaneous training
    • Large-scale and single-agent training
    • Multiple asset configurations utilize buildings, IoT, sensors, vehicles, autonomous systems, etc. This can also include large-scale vehicles, weapons and C2 systems.
  • Education, research and development
  • Industry 4.0 specific requirements

The construction of this city and campus-scale DT requires four significant areas that can iteratively increase but must begin at an agreed-upon starting point. These are: 

  1. Dialing in the fidelity required: Define from how big (The Universe) to how small (to an atomic Quark) the DT needs to be initially and moving forward.
  2. How much can you fake it: Data that feeds these twins are essential to the value of its modeling and simulation capabilities. When a set of data is not readily available, data must be created, which leads to two important questions: What percentage of synthetic data versus accurate data can be used within these twins? Can the real-world entity being twinned utilize Custom Synthetic Data Generation including Variational Autoencoder (VAE) and Generative Adversarial Network (GAN)?
  3. Content pipelines: Create the correct number of pipelines for content creation within the twin, including using 3D tools like Autodesk, Blender, Maya, etc.
  4. Multiple-layer integration: Cities and campuses utilize multiple layers to function. These layers are defined in many ways; for this paper, we will explain them per the image below.
Stacked layered viewed of a city that includes four layers: airspace, surface, terrain and subsurface.
Figure 1: Layer of City or Campus

Each layer of the twin contains hundreds to billions of data points, images, variables, physics and mathematical equations. As architects and stakeholders tune each layer's fidelity for the accuracy of its targeted set of use cases, they must consider how the model accuracy increases, the documented uncertainty decreases, and the input data pipelines and computational complexities plus costs increase. There is a point at which each layer's fidelity has reached its maximum cost/benefit value and any additional accuracy/uncertainty is not worth the incremental increase in complexity and accuracy.   

Each of these layers and points shall be described further in future whitepapers by WWT. 

Layer relations 

Now that a city or campus DT has been constructed, its initial fidelity agreed upon by its stakeholders, its uncertainty well documented, and its pipelines flowing with data labeled and cleansed, the next phase is the adhesion between each layer. These adhesions add to the actual value of the DT and how it is utilized. The image below is an initial DT currently under construction for an HBCU in Virginia.   

Graphical user interface, application

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Figure 2:  Utilization of Drone for Photogrammetry and LIDAR. Utilizing advancements in drones, photogrammetry, and LIDAR, this HBCU required two days' worth of FAA-approved flights capturing billions of point clouds and 1000s of high-definition imagery, allowing for the construction of each layer.  This layer is focused on layer 2 (Surface). 

The next phase is the construction of the other layers and their adhesions to work towards an operational, continuously updating DT (living Digital Twin).  Below are currently under-development water, fiber, telecom and sewer lines. 

A picture containing building, outdoor

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These connections between each building include pipe diameters, flow direction, and any metered water data used for fault detection and diagnostics (FDD).  They also include telecom taps, electrical meters, and other IoT sensors to monitor and manage. 

The next phase of DT construction will be the airspace layer. This layer is a decision criterion for the DT's stakeholders. Does it need to exist? At what height does it need to exist? How will data be collected to maintain the value of the DT? For instance, the university uses it to research and develop corridors and radar detection for traffic flow management, accident mitigation and low-level weather modeling. Similar to the subsurface layer, the airspace layer can be incredibly complicated and may require new IoT sensors for low-level weather modeling, for example. This can include wind and wind vorticity modeling, temperature and humidity modeling, etc. 

Digital twin automation and governance

Finally, the next phase of integration exists in the physical and digital worlds. With a completed DT in total production and providing answers, knowledge and new questions, it's time to automate changes in the digital world that, in near-real time, change the physical world. 

If a set of operations must be configured, modified or activated/deactivated for a campus or training range, for example, a designated individual typically makes the physical changes to the range, the campus or wherever the event is happening. Now with a fully functioning DT, a new layer is added between the DT and the physical world. Utilizing an automation layer, the DT user can make changes, modifications or updates within the DT and, through this new layer, change the physical environment. The goal is to reduce time, increase productivity and provide better governance between the DT and the physical environment. 

Stay tuned for an in-depth whitepaper describing the relationship and architecture between the physical city/campus, its DT and its automation/governance layer.   


A close-up of a circuit board

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Figure 3:  How a living Digital Twin can affect a Living City and Vice Versa 

How WWT can help  

The creation of city-scale DTs is a complex and multifaceted endeavor, requiring a plethora of tools and technologies to bring to fruition. From NVIDIA's Omniverse to Variational Autoencoders and Generative Adversarial Networks, each component plays a vital role in the development of Public Sector DTs. And that's where World Wide Technology comes in. We have the expertise to educate our customers and partners about this cutting-edge technology and are fully equipped to assist in the construction of these DTs. 

For more information on our DT capabilities, reach out to your account team or a WWT expert.

Ready to embark on the exciting journey of creating a Digital Twin? Contact Us