{"id":12404,"date":"2012-12-19T16:21:46","date_gmt":"2012-12-19T21:21:46","guid":{"rendered":"http:\/\/sciencebusiness.technewslit.com\/?p=12404"},"modified":"2012-12-19T16:21:46","modified_gmt":"2012-12-19T21:21:46","slug":"university-research-leads-to-battery-sorting-machine","status":"publish","type":"post","link":"https:\/\/technewslit.com\/sciencebusiness\/?p=12404","title":{"rendered":"University Research Leads to Battery Sorting Machine"},"content":{"rendered":"

\"Recycled<\/a>Research on artificial intelligence by a professor at Gothenberg University<\/a> in Sweden made possible a machine that sorts discarded household batteries and a company that developed and markets the system. Claes Stranneg\u00e5rd<\/a>, a researcher in logic and cognitive science at Gothenberg, applied his work on artificial intelligence to find a better way of sorting garbage.<\/p>\n

Stranneg\u00e5rd, who is also on the information technology faculty at Chalmers University of Technology in Gothenberg, conducts research on transparent neural networks, based on computational units and development rules that humans can understand and apply to real-world problems. In this case, the problem was sorting discarded household batteries by size, brand, type, and chemical content — e.g., nickel-cadium, lithium-ion — to make recycling the batteries easier and less costly, with environmental and economic benefits.<\/p>\n

Neural networks use artificial intelligence algorithms to learn and develop or refine their capabilities. The neural network needed for battery sorting learns to recognize some 2,000 different types of batteries by taking pictures of them from all possible angles. The system then can categorize loads of waste batteries by looking at each item with computer vision and comparing the item to the type of battery in memory. And the algorithms are robust enough to enable the system to deal with dirty or damaged batteries.<\/p>\n

Stranneg\u00e5rd founded the company Optisort<\/a> in Gothenburg in 2008 to translate this logic into an operational system. Last year, Optisort unveiled its first commercial battery sorting machine. The machine, says OptiSort’s CEO Hans-Eric Melin, has the potential to change the economics of battery recycling.<\/p>\n

“For each single battery, the system stores and spits out information about, for example, brand, model, and type,” says Melin. “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.” Melin adds that real-time data on recycled batteries could spark a new market for battery waste, where large volumes are traded online.<\/p>\n

Optisort has so far sold two battery sorting machines, one to Gothenberg recycling company Renova<\/a> — with whom Stranneg\u00e5rd collaborated in the validation of his initial research — and G&P Batteries<\/a>, a waste battery collection and recycling company in the U.K. The need to collect and recycle waste batteries has taken on additional urgency across Europe, with an EU directive<\/a> to recycle 25 percent of discarded portable batteries this year and 45 percent by 2016.<\/p>\n

The following promotional video from Optisort shows the battery sorting machine in action.<\/p>\n