AI identifies batteries in the waste stream

Lion Vision has developed a system that combines machine vision systems with machine learning techniques to detect, visualise and remove lithium-ion batteries and other hazardous items from the waste stream.

The Lion Vision system can analyse more than half a million images in a 24-hour window and detect more than 600 cylinder batteries per hour as the waste passes beneath it. Although the system currently focuses on detecting cylinder batteries, it can be programmed to detect more than 40 battery subtypes and other hazardous objects such as vapes.

Lion Vision’s detection system is in use at various sites across the UK, most notably at SWEEEP in Kent, where 100 tonnes of waste electrical and electronic equipment (WEEE) is processed every day. Amongst this waste, the Lion Vision system is detecting approximately more than 4500-cylinder batteries every day.


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