At first glance, the term Metaverse seems like something straight out of the Marvel Universe. In reality, the Microsoft Metaverse is the culmination and integration of a set of applications both in the intelligent cloud and at the edge — working in harmony to bring this concept to life right here on planet Earth. The vision of the Metaverse is to allow us to build a digital representation of anything in the physical world. This digitization could encompass something as small as a single product like an audio headset, to more complex systems like a farm, full manufacturing operation, or something as large as the energy grid. Once this digital representation is constructed, and bound to real-time analytics, we can learn and identify patterns, detect anomalies, and model potential scenarios and outcomes for that entity. However, before we discuss the real benefits of taking on such an enterprise, let’s discuss some of the key technologies required to make this all work. I’ve broken these out into three key areas — Data Collection & Digital Representation, Analysis & Modeling, and Visual Engagement.
Data Collection & Digital Representation
In order to digitize anything, you first have to capture the appropriate data/inputs of the physical system you are trying to bring into the digital world. This requires the use of sensor technologies, edge computing devices, and a few key cloud computing tools. These include Azure IoT, Azure Digital Twins, and Azure Maps.
- Azure IoT allows you to capture real-time data from the system you want to digitize. An example of this might be a sensor on a machine that’s tracking the real-time temperature of a piece of machinery.
- Azure Digital Twins allows the visual modeling of the complex relationships within the system you are trying to digitize.
- Azure Maps is a location platform that allows you to integrate a robust geospatial component into your digital twin.
Analysis & Modeling
Once that Digital Twin foundation is built, the next step is to leverage all of that data collection to better understand what’s currently going on in that entity or system, as well as leveraging predictive modeling to work on “what if” scenarios. The key technologies used here are Azure Synapse Analytics, Azure AI & Azure Autonomous Systems:
- Azure Synapse Analytics is a set of cloud-based data pipeline technologies that allow you to ingest data, perform some action to it (think ETL/ ELT), and then perform some set of simple to complex analytics on that data.
- Azure AI is also a portfolio of cloud services used by developers and data scientists. These services allow you to do really advanced predictive analysis and “what if” scenario exploration.
- Azure Autonomous Systems (Project Bonsai – currently in Preview) is a machine teaching service for creating intelligent industrial control systems using simulations. The promise of this service is to make the training and simulation technologies simpler so that teams of data scientists are no longer needed.
One of the ongoing challenges our industry has been trying to address is the reduction of end-user friction with the underlying technology. Using cutting-edge visualization technologies can allow for real-time and simple engagement with your digital twin. Technologies within the Microsoft Power Platform, as well as Microsoft Mesh and HoloLens, are key to making this a reality.
- Microsoft Power Platform allows anyone in the organization to build and interact with the data flowing through your environment. Using this platform, you’ll be able to develop customized workflows and process automation that can be trigger by specific events.
- Microsoft Mesh & HoloLens is very much the “space-age” part of this overall solution. You’ll be able to use augmented reality to visualize and interact with your digital twin.
While its admittedly an incredibly optimistic view on my part, I am convinced that the Microsoft Metaverse will have a tremendous impact on how we are going to be able to see and have an impact on our world. It will help us both visualize some of our toughest challenges as well as model and test potential solutions to these problems in a way that was previously not possible. Whether we’re discussing climate change, a global pandemic, or optimizing a food supply chain in a third-world country, we now have the tools to give us a fighting chance.