Data processing these days is exhibiting a split personality. ‘Cloud’ computing grabs the headlines for sheer scale and computing power, while ‘edge’ computing puts the processing at the ‘coal face’ ...

Electrical power systems engineers need practical methods for predicting solar output power under varying environmental conditions of a single panel. By integrating an Arduino-based real-time data ...

Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

Scientists in Japan have developed a new, highly efficient method for designing wireless power transfer (WPT) systems. Based on machine learning, the method enables a system to maintain stable voltage ...

Many people have begun experimenting with using machine learning in embedded systems as the two technologies have become more prominent in today’s society. That approach allows for overcoming many of ...

This system utilizes machine learning algorithms to optimize the operation of particle accelerators, reducing manual intervention and enhancing precision in real-time control. By integrating virtual ...

Why it matters: Google is designing an operating system for embedded applications that runs machine learning algorithms. KataOS' main targets are security and privacy protection, working with open ...