New system launched to extract lithium-ion batteries from waste streams

 

lithium-ion-battery

New system launched that visualises and extracts lithium-ion batteries and other hazardous items from waste streams using advanced vision systems and machine-learning technologies.

A partnership between University of Manchester academics and Lion Vision, a North West-based Artificial Intelligence (AI) specialist, developed the Lion Vision system.

University of Manchester said the system uses real-time analytics to identify where the flammable batteries are in the waste stream and how they should be removed.

LionVision
University of Manchester said the system uses real-time analytics to identify where the flammable batteries are in the waste stream and how they should be removed.

The team of entrepreneurs behind Lion Vision, along with the University, successfully applied to the Knowledge Transfer Partnerships (KTP) programme run by Innovate UK and was given a grant of more than £125,000 to assist with the project.

They partnered with Professor Hujun Yin, Professor of Artificial Intelligence in the School of Engineering, as part of the development process.

As waste passes underneath it, the Lion Vision system can analyse over half a million images in a 24-hour window and detect more than 600 cylinder batteries per hour, University of Manchester said.

While the system is currently focused on detecting cylinder batteries, the University said it can be programmed to detect over 40 battery sub-types and other hazardous objects such as vapes.

The detection system is now in place at a range of sites across the UK, including at SWEEEP in Kent which processes 100 tons of waste electrical and electronic equipment (WEEE) per day.

I have no doubt that the system created by the partnership and the team at Lion Vision will have a significant impact on the waste industry.

Typically, amongst this waste, the Lion Vision system is detecting more than 4500-cylinder batteries daily, University of Manchester said.

Hujun Yin, Professor of Artificial Intelligence, based in the Department of Electrical and Electronic Engineering, commented: “My work in AI and vision systems has often given me insight into challenges that society faces, and this project was no exception.

“While policy change and progress should be pursued, we cannot underestimate the environmental damage that is being caused by lithium-ion batteries.

“It is our responsibility to find engineering solutions to these problems. I have no doubt that the system created by the partnership and the team at Lion Vision will have a significant impact on the waste industry.”

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