Edge Computing, Embedded Systems

Create value from data: Using HMIs as intelligent edge devices

Human-machine interfaces (HMIs) are evolving beyond basic visualization devices to become edge-located, data handling, and analytical powerhouses. See 5 modern HMI attributes.

Executive Brand Video Series—Learn How Thought Leaders at Stratus are Responding to COVID-19

Jason Andersen, vice president strategy and product management at Stratus Technologies, discusses how they are responding to the COVID-19 pandemic.

Automation controllers, edge computing

Which devices to use? A multi-tasking controller combines functions of a PC-based software controller with visualization, PC applications, and input/output connections. Combining a scalable human-machine interface (HMI) system, supervisory control and data acquisition, and other functions can add edge functionality.

Should I use an edge controller, PLC, or PAC?

Industrial automation end users are finding edge control technologies excel at familiar programmable logic controller (PLC) and programmable automation controller (PAC) applications while delivering future-proof computing and communication options.

Automation meets edge computing

Combining a scalable human-machine interface (HMI) system and supervisory control and data acquisition with additional edge functionality gives machine and plant designs a high degree of flexibility and adaptability to quickly react to changing market environments and maintain fast innovations cycles.

Big Data analytics moves right to the edge

The implications of the introduction of the IEEE 802.3cg standard for industrial automation and what it might mean for 4-20mA or HART systems.

Edge computing terms and skills

Six edge computing questions to ask about data collection, networking and control systems.

Edge computing offers 4-step pathway to digital transformation

Special Report: Living on the edge: Putting computing power close to the process reduces control system latency, creates a distributed architecture, and can integrate machine learning (ML) and artificial intelligence (AI) capabilities for faster, more flexible optimization and expand and improve use of cloud services. See four steps toward edge computing.

Convolutional neural networks help embedded vision applications

Convolutional neural networks (CNNs) have the ability to replicate the human thought process and use embedded vision to automate those processes.

Skills for the edge computing revolution

Edge computing is becoming more prevalent, and it’s imperative for engineers to get in on the action. Learn four skills engineers can develop to be better prepared.