Sign up for our daily Newsletter and stay up to date with all the latest news!

Subscribe I am already a subscriber

You are using software which is blocking our advertisements (adblocker).

As we provide the news for free, we are relying on revenues from our banners. So please disable your adblocker and reload the page to continue using this site.

Click here for a guide on disabling your adblocker.

Sign up for our daily Newsletter and stay up to date with all the latest news!

Subscribe I am already a subscriber

UW-Stout professors use AI for fruit selection, materials science

Researchers at the University of Wisconsin-Stout are testing applications of artificial intelligence, such as sorting fruit by freshness and maximizing the strength of lattice structures in protective materials.

While opinions on artificial intelligence technology in the world seem to be incredibly varied, two researching professors at UW-Stout see potential for application.

Yuan Xing and Anne Schmitz, both assistant professors in the Engineering and Technology Department, both incorporate a neural network machine learning process as a way for AI to learn their tasks. Each of their individual research projects focus on a different topic, but they represent two of the many different AI-based research initiatives happening at the university level.

For Xing, he said his research tests the application of AI to differentiate and evaluate fresh fruit and produce. "This project is to improve the smart manufacturing system," Xing said. "We're going to rely on an AI model to control multiple robots. It is also implemented as an automatic control system, or automation, in smart manufacturing."

By using this technology and conducting research on it, Xing said their hope is to create a more accurate system to sort fruits by category or freshness. "We can save human labor, so we don't need a human to literally check every product … We can also speed up the production," he said.

On top of that, Xing also said the system could increase the sustainability of produce, as the more accurate measuring of the AI model can lead to less produce discarded and wasted by that means.

Xing said the current production line does not have a fully automated AI detection system in place, but there is an opportunity to implement the model in industrial-level robots with a prototype created through his research.

One concern that people may have with this technology is that it could lead to jobs being lost to artificial intelligence, but Xing said he does not necessarily believe that will be the case.

"That is a very important thing people need to discuss," Xing said. "Because, some people may think that if robots can replace human labor, then people are losing jobs. I will say if they use a robot, you can train human labor to learn how to manipulate the robot … The labor no longer needs to do the job manually, they can control the AI model or maintain the robot to do the job."

Xing also said he is seeing more and more of his colleagues take up AI in their research, especially in his department, where they look at solving modern engineering problems.


Publication date: