White paper on optimal cloud, edge use for industrial machine vision applications published

The Industry IoT Consortium (IIC)  published the Optimal Use of Cloud and Edge in Industrial Machine-Vision Applications white paper. The paper is designed as a guide for developers looking to integrate machine vision with industrial cloud and edge computing applications.

“With advances in technology, industrial machine vision is becoming increasingly sophisticated. For example, today you can perform AI vision analysis directly on a camera. You can also process this data on a nearby computer, an on-premises server, or remote data center,” said Daniel Young, IIC Technology Working Group Co-Chair and Senior Manager at Toshiba in a press release. “Understanding where image processing should occur is an engineering decision based on many different factors. For example, cloud computing offers industrial applications flexibility and scalability for machine learning models, while edge computing is best for real-time industrial tasks.”

The white paper covers the following sections:

• Applications of Industrial Machine Vision, which gives a broad description of how companies use industrial machine vision.

• Edge Computing in Industrial Machine Vision, which provides an overview of applying edge computing to industrial machine vision applications.

• Cloud Computing in Industrial Machine Vision, which discusses cloud computing in industrial machine vision.

• Deciding Where the Edge Lies in Industrial Machine Vision, which talks about typical edge computing configurations that incorporate industrial machine vision.

– Edited from an Industry IoT Consortium (IIC) press release by CFE Media and Technology. IIC is a CFE Media and Technology content partner.

ONLINE extra

Download the Optimal Use of Cloud and Edge in Industrial Machine-Vision Applications whitepaper from the IIC website for more information and a complete list of authors.

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