UPDATED 19:12 EDT / DECEMBER 17 2021

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Esri’s integration with AWS and geospatial AI power real-world use cases for locational data

When the COVID-19 virus began to spread widely across the U.S. early in 2020, concerned citizens turned to an online database set up and maintained by Johns Hopkins University of Medicine for the most up-to-date data. That useful interface continues to rely heavily on information supplied by the geospatial pioneer Environmental Systems Research Institute Inc., more commonly known as Esri.

ArcGIS is Esri’s family of geographic information system services that leverages mapping software to track critical data across the world.

“GIS is being used for real-world problems,” said Jay Theodore (pictured, right) chief technology officer for enterprise and artificial intelligence at Esri. “We build geospatial infrastructure that’s built for the cloud, built for the edge. We help our customers solve very complex challenges by bringing location intelligence into the mix.”

Theodore spoke with Dave Vellante, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during AWS re:Invent. He was joined by David Cardella (pictured, left), group product manager for developer technologies at Esri, and they discussed the firm’s partnership with Amazon Web Services Inc. and the rise of geospatial AI. (* Disclosure below.)

Locational data for apps

In June, AWS announced that Amazon Location Service would become generally available for developers. The fully managed solution helps developers add a wide range of locational data points to applications, using technology provided by Esri.

“It brings location and spatial intelligence directly into a developer’s AWS dashboard,” Cardella noted. “They now get the power of Esri services and location intelligence right at their fingertips.”

Satellite, aerial and drone imagery is being collected today at a rate that makes it virtually impossible to analyze using humans or traditional approaches. This has led Esri to develop new tools for geospatial AI, an ability to apply machine and deep learning methods to the analysis of sensor-generated, location-based data.

“On the ground, above the ground, under the ground, all of these sensors are bringing in data,” Theodore said. “Human interpretation is pretty challenged, so that’s where AI comes in to augment the intelligence that we have in terms of extracting information. AI has come to the edge.”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of AWS re:Invent. (* Disclosure: AWS Public Sector sponsored this segment of theCUBE. Neither AWS nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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