Edge Computing, Embedded Systems

Image courtesy: Brett Sayles
Edge Computing, Embedded Systems October 11, 2022

Formula tackles complex moral decision-making for AI

A blueprint for creating algorithms that more effectively incorporate ethical guidelines into artificial intelligence (AI) decision-making programs has been developed.

By Matt Shipman
Edge Computing, Embedded Systems October 7, 2022

Is control theory better than AI for improving plant performance?

Understand the strengths and weaknesses of artificial intelligence (AI) and machine learning (ML) versus control theory, particularly model predictive control (MPC) for improving process and manufacturing applications and operations.

By John F. Carrier
Edge Computing, Embedded Systems October 5, 2022

Smarter energy measurements, faster, using AI

Engineers use artificial intelligence (AI) to magnify domain expertise and significantly cut time to end user.

By Dr. Bas Kastelein and Dr. Richard Ahlfeld
Edge Computing, Embedded Systems October 4, 2022

Using edge machine learning for anomaly detection, predictive maintenance

More powerful and cost-effective computing combined with advancements in artificial intelligence (AI) are helping predictive maintenance to detect anomalies, which predicate a maintenance action when needed. Edge computing brings decision-making and intelligence as close to the process as possible.

By Matt Dentino and Mitsuo Baba
Edge Computing, Embedded Systems October 4, 2022

How AI, ML and neural networks differ and work together

While similar, artificial intelligence (AI), machine learning (ML) deep learning and neural networks have specific tasks and roles.

By Ted Thayer
IMTS sustainability at edge
Edge Computing, Embedded Systems September 19, 2022

Navigating the road to sustainability at the edge

Achieving sustainability at the edge looks different for every organization. There are key steps to help narrow down which path to take to reach those sustainability goals.

By Morgan Green
Edge Computing, Embedded Systems September 14, 2022

Improving worker optimization on the factory floor with artificial intelligence

Artificial intelligence (AI) can be used to enhance worker productivity by gathering information about their work performance and turning it into actionable data.

By Chris Vavra
Edge Computing, Embedded Systems September 14, 2022

Automation and AI should be embraced, not feared

Artificial intelligence (AI) and automation have raised concerns about humans being replaced by machines in manufacturing, but the truth is they will add better and more meaningful jobs for humans.

By Morgan Green
Courtesy: CFE Media
Edge Computing, Embedded Systems September 13, 2022

Collaborative machine learning preserves privacy

Federated learning is a collaborative method for training a machine-learning model that keeps sensitive user data private.

By Adam Zewe
Figure 2: A complete and fully automated solution inspects solder joints at BSH. Using Micropsi’s MIRAI, the solution was trained through human demonstration instead of programmed. Instead of manually guiding the probe to each individual solder joint, employees can now concentrate on value-creating activities. Courtesy: Micropsi Industries
Edge Computing, Embedded Systems September 5, 2022

Software improves AI, automation flexibility

Software-based artificial intelligence (AI) can be used to give robots abilities that allow them to straddle the flexibility gap between small batch manufacturing and high-volume automation.

By Matt Jones