Esri boosts digital twin tech for its GIS mapping tools

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Geographic information system (GIS) mainstay Esri is looking to expand its stake in digital twin technologies through significant updates in its product portfolio. As it announced at its recent user conference, the company is updating complex data conversion, integration, and workflow offerings to further the digital twin technology mission.

In fact, GIS software is foundational to many digital twin technologies, although that is sometimes overlooked as the nebulous digital twin concept seeks greater clarity in the market.

Esri’s updates to its ArcGIS Velocity software promise to make diverse big data types more readily useful to digital twin applications. At Esri User Conference 2021, these enhancements were also joined by improvements in reality capture, indoor mapping, and user experience design for digital twin applications.

Reality capture is a key to enabling digital twins, according to Chris Andrews, who leads Esri product development in geo-enabled systems, intelligent cities, and 3D. Andrews gave VentureBeat an update on crucial advances in Esri digital twins’ capabilities.

“Reality capture is a beginning — an intermittent snapshot of the real world in high accuracy 3D, so it’s an integral part of hydrating the digital twin with data,” he said. “One area we will be looking at in the future is indoor reality capture, which is something for which we’re hearing significant demand.”

What is reality capture? One of the most important steps in building a digital twin is to automate the process of capturing and converting raw data into digital data.

There are many types of raw data, which generally involve manual organization. Esri is rapidly expanding workflows for creating, visualizing, and analyzing reality capture content from different sources. This includes point clouds (lidar), oriented and spherical imagery (pictures or circular pictures), reality meshes, and data derived from 2D and 3D raster and vector content such as CAD drawings.

For example, Esri has combined elements it gained from acquiring SiteScan and nFrames over the last two years with its in-house developed Drone2Map. Esri also created and is growing the community around I3S, an open specification for fusing data captured by drones, airplanes, and satellites, Andrews told VentureBeat.

ArcGIS Velocity handles big data

Esri recently disclosed updates to ArcGIS Velocity, its cloud integration service for streaming analytics and big data.

ArcGIS Velocity is a cloud-native, no-code framework for connecting to IoT data platforms and asset tracking systems, and making their data available to geospatial digital twins for visualization, analysis, and situational awareness. Esri released the first version of ArcGIS Velocity in February 2020.

“Offerings like ArcGIS Velocity are integral in bringing data into the ArcGIS platform and detecting incidents of interest,” said Suzanne Foss, Esri product manager.

Updates include stateful real-time processing introduced in December 2020, machine learning tools in April and June 2021, and dynamic real-time geofencing analysis in June 2021. The new stateful capabilities allow users to detect critical incidents in a sensor’s behavior over time, such as change thresholds and gap detection. Dynamic geofencing filters improve the analysis between constantly changing data streams.

Velocity is intended to lower the bar for bringing in data from across many different sources, according to Foss. For example, a government agency could quickly analyze data from traffic services, geotagged event data, and weather reports to make sense of a new problem. While this data may have existed before, it required much work to bring it all together. Velocity lets users get mashup data into new analytics or situational reports with a few clicks and appropriate governance. It is anticipated that emerging digital twins will tap into such capabilities.

Building information modeling tie-ins

One big challenge with digital twins is that vendors adopt file formats optimized for their particular discipline, such as engineering, operations, supply chain management, or GIS. When data is shared across tools, some of the fidelity may be lost. Esri has made several advances to bridge this gap such as adding support for Autodesk Revit and open IFC formats. It has also improved the fidelity for reading CAD data from Autodesk Civil 3D and Bentley MicroStation in a way that preserves semantics, attribution, and graphics. It has also enhanced integration into ArcGIS Indoors.

Workflows are another area of focus for digital twin technology. The value of a digital twin comes from creating digital threads that span multiple applications and processes, Andrews said. It is not easy to embed these digital threads in actual workflows.

“Digital twins tend to be problem-focused,” he said. “The more that we can do to tailor specific product experiences to include geospatial services and content that our users need to solve specific problems, the better the end user experience will be.”

Esri has recently added new tools to help implement workflows for different use cases.

  • ArcGIS Urban helps bring together available data with zoning information, plans, and projects to enable a digital twin for planning applications.
  • ArcGIS Indoors simplifies the process of organizing workflows that take data from CAD tools for engineering facilities, building information modeling (BIM) data for managing operations, and location data from tracking assets and people. These are potentially useful in, for example, ensuring social distancing.
  • ArcGIS GeoBIM is a new service slated for launch later this year that will provide a web experience for connecting ArcGIS and Autodesk Construction Cloud workflows.

Also expected to underlie digital twins are AR/VR technologies, AI, and analytics. To handle that, Esri has been working to enable the processing of content as diverse as full-motion imagery, reality meshes, and real-time sensor feeds. New AI, machine learning, and analytics tools can ingest and process such content in the cloud or on-premises.

AI digital twin technology farm models

The company has also released several enhancements to organizing map imagery, vector data, and streaming data feeds into features for AI and machine learning models. These can work in conjunction with ArcGIS Velocity either for training new AI models or for pushing them into production to provide insight or improve decision making.

For example, a farmer or agriculture service may train an AI model on digital twins of farms, informed by satellite feeds, detailed records of equipment movement, and weather predictions, to suggest steps to improve crop yield.

Taken as a whole, Esri’s efforts seek to tie very different kinds of data together into a comprehensive digital twin. Andrews said the company has made strides to improve how these might be scaled for climate change challenges. Esri can potentially power digital twins at “the scale of the whole planet” and address pressing issues of sustainability, Andrews said.

Like so many events, Esri UC 2021 was virtual. The company pledged to resume in-person events next year.

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