Do industrial edge applications use enough sensors, and are they delivering enough data to be effective? Learn more in a May 8 webcast, archived for a year, “Edge sensors, data gathering: IIoT automation sensors to fit application needs.”

Learning Objectives
- Understand industrial Internet of Things (IIoT) sensors and industrial sensors and how they’re used in edge communications applications.
- Learn how to connect more sensors for industrial edge applications, economically.
- See how industrial data without context isn’t useful information.
Edge sensors and IIoT automation sensor insights
- Industrial Internet of Things (IIoT) sensors and industrial sensors are used in edge communications applications.
- More sensors can be connected economically for use in industrial edge applications.
- Industrial data without context isn’t useful information.
Instructors for the May 8 Control Engineering webcast, “Edge sensors, data gathering: IIoT automation sensors to fit application needs,” expect to answer the following questions:
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Edge applications often receive optimal controller selection to ensure best performance, but do they have enough high-quality sensors for appropriate data gathering and analysis?
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Are industrial Internet of Things (IIoT) automation initiatives helping or hurting data gathering and how?
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Is sensor information getting where it needs to in reliable form for prompt and reliable decisions?
The webcast is archived for a year. Instructors for the course, for one RCEP professional development hour for those listening live, will be:
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Michael Bowne, executive director of PI North America and deputy chairman for PROFIBUS & PROFINET International (PI) on a global scale. https://us.profinet.com
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Paul Brooks, member of the ODVA Distributed Motion and Time Synchronization Special Interest Group. ODVA.org
IIoT sensors, industrial sensors, edge communications applications
Learning objectives for the course are to explore how to know when an application has enough sensors of appropriate type and quality to meet IIoT automation goals; understand how IIoT automation sensor needs may differ from traditional automation sensor needs; and review sensor sampling rate, signal quality and other things that can affect sensor measurements. Presenters also are expected to provide examples of sensor use in IIoT automation applications and share benefits of how appropriate sensor selection and use are helping.
Connect more sensors for industrial edge applications, economically
In notes for the webcast, Bowne said, “When using IoT technologies, the automation, production and operations managers must work together with the IT department. Conflicts of objectives are preprogrammed here, since the production thinking (24/7 operation, high quality, no downtime) is contrary to that of IT (regular updates, server maintenance, no real-time, data security …) The big data database forms the knowledge base for analyzing the data. It has different sources: IO-Link devices, controllers, weather, currency rates, depending on the application. ‘Cloud’ does not necessarily mean a database on the Internet, there are also ‘private cloud,’ ‘hybrid cloud’ etc.”
Bowne said that using an IO-Link network to the “last meter” sensors and actuators are directly accessible because they use bidirectional serial communication for both cyclic and acyclic data rather than just a simple input or a simple output.
“As memory and computing power have gotten really, really small and really, really cheap, we are starting to see devices in the market that have a lot more capability in them,” Bowne said.
“Now you can make a device smart – so it knows, for example, not only if a box is present or not, but if it is a red box or if it is a blue box. The device may even know how many red boxes went by and how many blue boxes went by. But you aren’t going to put a $5 Ethernet chip in a $15 proximity sensor. It makes no sense.” IO-Link is a way to provide cost-effective access to all data in intelligent devices, he suggested.
Brooks, in notes for the webcast, discussed data collection and analytics.
“Every control system, every device is like an iceberg. The process data that is seen by the controller is just the 5% that pokes above the surface. And that’s all that the operator needs to see. But the really interesting information, the data that helps you know what might happen, or what has happened that might affect future operation, can mostly be found under water.”
He said that controls vendors, typically document information well, but noted “You need to do the work selecting and gathering that data and contextualizing it in your application.
“And that brings me to context. Information out of context, without any metadata, is just noise. A sensor doesn’t need to know where it is, and a control systems engineer writing code for a machine doesn’t need to know how a sensor works, just its outcome. You and your value chain need to do the work to contextualize this dark data before its full value can be exploited. The more metadata that you provide, the more tools that you give analytic software to provide actionable insights and to reconstruct the tribal knowledge lost when that old technician entered well-earned retirement.”
Mark T. Hoske is content manager, Control Engineering, CFE Media and Technology, [email protected], and moderator for this webcast.
KEYWORDS: Edge sensors, IIoT sensors for edge applications
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