Edge Computing, Embedded Systems

Courtesy: Cornell University
AI and Machine Learning February 8, 2022

Physical systems perform machine-learning computations

Cornell researchers are training physical systems to perform machine-learning computations such as identifying handwritten numbers and spoken vowel sounds.

By David Nutt
Courtesy: CFE Media and Technology
AI and Machine Learning February 4, 2022

Conversational IoT and AI powered by “chatbots”

Even in industry, branding and personality play a role

By Ken Herron
Courtesy: Jeff Fitlow, Rice University
AI and Machine Learning February 2, 2022

Machine learning fine-tunes flash graphene

Rice University scientists are using machine-learning techniques to streamline the process of synthesizing graphene from waste through flash Joule heating. 

By Mike Williams
Courtesy: North Carolina State University
AI and Machine Learning January 30, 2022

Technique improves AI ability to understand 3D space using 2D Images

North Carolina State University researchers have developed a technique called MonoCon that is designed to improve the ability to identify 3D objects using 2D images.

By Matt Shipman
Courtesy: CFE Media and Technology
AI and Machine Learning January 19, 2022

Solving big problems via algorithms enhanced by 2D materials

Important optimization algorithms that are designed to solve large-scale problems such as supply chain logistics can be boosted from 2D materials.

By Jamie Oberdick
Courtesy: Peter Galan, retired control software engineer
Embedded Systems, Edge Computing January 10, 2022

Top 5 Control Engineering articles January 3-9, 2022

Articles about embedded systems, automated pressure testing, the 2022 SIY winners, PLCs' role in automation and no-code robotics were Control Engineering’s five most clicked articles from January 3-9, 2022. Miss something? You can catch up here.

By Chris Vavra
Courtesy: Beckhoff Automation
AI and Machine Learning January 10, 2022

Seven tips for implementing machine learning in controls environments

Machine learning (ML) applications are evolutionary by nature, so it is important to understand how they work and keep looking for new ways to apply them to deliver an automation advantage.

By Daymon Thompson
Automated production process. The UR10e places a metal ring on a conveyor belt.
AI and Machine Learning January 10, 2022

The future of manufacturing production is here today

Fully exploit the potential of robotics with AI

By Maximilian Mutschler
Courtesy: USC Viterbi
AI and Machine Learning December 12, 2021

Advances in brain-inspired computing

USC Viterbi researchers have developed an efficient and sustainable hardware device for artificial intelligence (AI) and machine learning (ML) applications.

By Amy Blumenthal
Courtesy: Yash Technologies
AI and Machine Learning December 9, 2021

How the AIoT makes factories “smart”

The Artificial Intelligence of Things (AIoT) can integrate different types of data and information to give manufacturers a better picture of how everything works in facilities. See four AIoT factors responsible for smart factory growth.

By Sacheen Patil