E-commerce giant Amazon is building a computer vision-based grading solution for food products such as onions and tomatoes. The machine learning-based approach analyses produce images to detect defects such as cuts, cracks and pressure damage. It can carry out millions of assessments per day at a cost that is far below compared to any other method, said a top Amazon scientist.
“Quality is one of the key drivers of fruit and vegetable purchasing decisions and a critical factor in achieving customer satisfaction,” said Rajeev Rastogi, vice president, machine learning, Amazon India at the company’s Smbhav event. “Having humans grade the quality of fruits and vegetables by manually examining each individual piece of produce like tomato or onion is not scalable to millions of quality assessments per day.”
Amazon plans to develop a conveyor belt based automatic grading and packing machine. It would leverage hardware and machine learning to pack produce into predetermined quality grades such as premium-grade A. The gradient pack machine will reduce grading cost by 78 per cent compared to manual grading.
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