Learn When to Implement Cloud vs. Edge in Industrial AI
February 23, 2023
News
Boston, Massachusetts. The Industry IoT Consortium (IIC) released its Optimal Use of Cloud and Edge in Industrial Machine-Vision Applications whitepaper. Readers will read a simple guide to help them through the development of integrated machine vision along with industrial cloud and edge computing solutions.
“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. “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.”
Highlights Include:
Applications of Industrial Machine Vision
- Broad description of how companies use industrial machine vision
Edge Computing in Industrial Machine Vision
- Overview of applying edge computing to industrial machine vision applications
Cloud Computing in Industrial Machine Vision
- Cloud computing in industrial machine vision.
Deciding Where the Edge Lies in Industrial Machine Vision
- General edge computing configurations that incorporate industrial machine vision.
View the Optimal Use of Cloud and Edge in Industrial Machine-Vision Applications whitepaper on the IIC website for more information and a complete list of authors, iiconsortium.org.
Chad Cox. Production Editor, Embedded Computing Design, has responsibilities that include handling the news cycle, newsletters, social media, and advertising. Chad graduated from the University of Cincinnati with a B.A. in Cultural and Analytical Literature.
