The Edge Impulse And Realpars Establish Automation Technology Content Partnership

Edge Impulse and RealPars collaboration will help raise awareness of the practice and push it forward.

FREMONT, CA: Industrial settings are increasingly turning to predictive maintenance as one of the most sought-after upkeep methods. It is possible to detect anomalies in machinery before breakdowns occur using artificial intelligence algorithms, embedded sensors, and onboard computing. This technique allows for just-in-time repair or replacement so that machine uptime increases and costly shutdowns decrease through ML algorithms, embedded sensors, and onboard computing.

Many leading industrial education companies in North America, including RealPars, recognized for delivering cutting-edge industrial education, and Edge Impulse, an innovative machine learning platform, unveiled they are working together to deliver ground-breaking content for the development of advanced manufacturing tools and techniques.

In the first phase of the partnership, RealPars will leverage Edge Impulse's machine learning tools to demonstrate how Edge Impulse's machine learning tools can help industrial equipment operate more efficiently and help improve maintenance cycles through predictive maintenance programming. 

The Edge Impulse platform, the industry's leading development platform for machine learning on edge devices, allows developers to rapidly and easily create and optimize solutions based on real-world data without coding knowledge. Through its cloud-based platform, the company streamlines everything from collecting and structuring datasets to designing machine learning algorithms with ready-made building blocks, testing the models with real-time data, to deploying the fully optimized and production-ready results to target devices at the edge. With Millions of developers building smarter devices for billions of people worldwide, the Edge Impulse development platform, which is already being used by thousands of companies, stands to unlock massive value across a multitude of industries, including manufacturing and many others.