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Embedded Computing


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Real-Time Digital Twins: The Next Generation in Streaming Analytics

  • 13th December 2021

The goal of real-time streaming analytics is to get answers fast. Mission-critical applications
that manage large numbers of live data sources need to quickly sift through incoming
telemetry, assess dynamic changes, and immediately pinpoint emerging issues that need
attention.

Examples abound: a telematics application tracking a fleet of vehicles, a vaccine
distribution system managing the delivery of thousands of shipments, a security or safety
application analyzing entry points in a large infrastructure (physical or cyber), a healthcare
application tracking medical telemetry from a population of wearable devices, a financial
services application watching wire transfers and looking for potential fraud — the list goes
on. In all these cases, when a problem occurs (or an opportunity emerges), managers need
answers now. Streaming analytics using real-time digital twins meets this challenge.

In this eBook, “Real-Time Digital Twins: The Next Generation in Streaming Analytics,” you will learn:

• What are real-time digital twins?
• Advantages over conventional streaming analytics
• Aggregating state data created by real-time digital twins
• Geospatial mapping for real-time digital twins
• Digital twins and real-time digital twins: What’s the difference?

Brought to you by:

 

 

 

Tags: Data platforms Embedded Computing Business Resources White Papers Sponsor Content

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