Esri Boosts Digital Twin Tech For Its Gis Mapping Tools | Livingsights

Esri Boosts Digital Twin Tech For Its Gis Mapping Tools

Esri Boosts Digital Twin Tech For Its Gis Mapping Tools
Written by Varsha Pednekar

Esri’s updates to its ArcGIS Velocity software promise to make diverse big data types more readily useful to digital twin applications.

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.

News Source: Venture Beat