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Using AI to reduce food waste - Florian Goebels

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As Canadians, we waste every day a total of 2.4M potatoes, 1.2M tomatoes, 1.2M apples, and many more. More than half of all food produced in Canada is lost or wasted. This totals to an equivalent to 9.8 million tons of CO2 or 2.1 million cars on the road (~10% of cars in Canada).

How can we leverage current AI technologies to tackle this problem? Here I suggest an IoT solution to retrofit existing fridges to smart fridges. I combine image recognition and sensors to conveniently track food waste and consumption. It will support calculating CO2 impact based on each individual’s food consumption, encouraging users to change their consumption lifestyle to be more environmentally friendly while saving them money.

Bio: Florian has more than 7 years of experience in Data science. In 2014 he received his Ph.D. in Computer science from the Technical University of Munich, after which he joined the University of Toronto as a postdoctoral fellow. During Florian’s academic career his focus was on developing and implementing top-notch custom machine learning solution.

Prior to joining BMO Florian worked as a researcher at LoyaltyOne’s innovation lab where he investigates novel applications of deep learning on Canada’s largest retail dataset with the goal to improve your shopping experience.

Florian’s goal as a member of BMO’s Data Cognition Team is to use his acquired ML expertise to deliver the best possible machine learning solution to your specific problem.

In his free time, Florian actively participates in the Toronto AI environment and he explores new ML technologies and their applications.