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In today’s world of the Industrial Internet of Things (IIoT) and emerging artificial intelligence (AI) solutions, there’s a growing need to share operational technology (OT) data from supervisory control and data acquisition (SCADA) systems and integrate it with the business information typically found in information technology (IT) systems. Much of this data originates from legacy control hardware performing dedicated functions that aren’t directly compatible with evolving IT environments supporting AI and other initiatives.
What are the key considerations for bridging this data divide to enable new applications in a safe, efficient and economical way? Control Amplified spoke with Barry Baker, vice president of Trihedral Engineering, about the benefits of adopting edge-based solutions for existing applications.
 By ControlGlobal
By ControlGlobal4
88 ratings
In today’s world of the Industrial Internet of Things (IIoT) and emerging artificial intelligence (AI) solutions, there’s a growing need to share operational technology (OT) data from supervisory control and data acquisition (SCADA) systems and integrate it with the business information typically found in information technology (IT) systems. Much of this data originates from legacy control hardware performing dedicated functions that aren’t directly compatible with evolving IT environments supporting AI and other initiatives.
What are the key considerations for bridging this data divide to enable new applications in a safe, efficient and economical way? Control Amplified spoke with Barry Baker, vice president of Trihedral Engineering, about the benefits of adopting edge-based solutions for existing applications.

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