‘I got the idea at home when I was sorting rubbish,’ said Claes Strannegård, an AI researcher at Gothenburg University and Chalmers University of Technology. ‘I thought it should be possible to do it automatically with AI.’
The sorting of up to 10 batteries a second is made possible by the machine’s so-called neural network, which was trained to recognise about 2,000 different types of batteries by taking pictures of them from all possible angles.
As the batteries are fed into the machine via a conveyor belt, they are visually inspected by the machine via a camera.
The neural network identifies the batteries in just a few milliseconds by comparing the picture taken with pictures taken earlier.
The network is self-learning and robust, making it possible to recognise batteries even if they are dirty or damaged.
Once the batteries have been identified, compressed air separates them into different containers according to chemical content, such as nickel-cadmium or lithium.
‘For each single battery, the system stores and spits out information about, for example, brand, model and type. This allows the recycler to tell a larger market exactly what types of material it can offer, which we believe may increase the value through increased competition,’ said Hans-Eric Melin, chief executive officer of Gothenburg-based Optisort, a company founded by Strannegård to develop the machine.
Melin added in a statement that real-time battery data could spark a new market for battery waste, where large volumes are traded online.
So far, the company has delivered two machines — one to Renova in Gothenburg (where half of all the batteries collected in Sweden are sorted) and one to G&P Batteries in the UK.
The interest in Optisort and its machine is rising, and Strannegård, who founded the company, believes AI could eventually be employed to help sort all types of waste.
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