Latest Tomra Sorting e-book details the potential artificial intelligence holds for the recycling industry

By imitating human learning, deep learning shows promise to find solutions to sorting challenges where none currently exist

Deep learning is on the rise in the recycling industry, according to the new eBook “Harnessing the Potential of AI” from the global leader in sensor-based sorting, TOMRA Sorting Recycling. Dispelling a common misconception about AI, this latest TOMRA eBook chronicles the long, 30-year history and contributions AI has already made to the recycling industry, as well the bright future that lies ahead.

“In the months and years to come, those in the recycling industry will hear much more about deep learning, a powerful component of AI,” says Daniel Bender, Technical Manager, Deep Learning for TOMRA Sorting. “Deep learning shows the promise of providing solutions for the industry’s most complex sorting challenges. Recycling operations at the forefront of using AI to sort material stand to gain a significant advantage over companies who do not.”

The free-to-download eBook goes into detail of how deep learning works and learns to identify materials to resolve problems not solvable with classical machine learning. The book claims deep learning holds the key for achieving more consistent detection rates than manual sorting, elevating material purity while lowering costs.

To download your English copy of the new TOMRA eBook on AI and Deep Learning, please visit https://solutions.tomra.com/ai-ebook.   

TOMRA Sorting Recycling designs and manufactures sensor-based sorting technologies for the global recycling and waste management industry. Over 6,000 systems have been installed in more than 100 countries worldwide. Moreover, we have more than 6,000 units installed.

Responsible for developing the world’s first high capacity near infrared (NIR) sensor for waste sorting applications, TOMRA Sorting Recycling remains an industry pioneer with a dedication to extracting high purity fractions from waste streams that maximize both yield and profits.