AI model to separate low-quality food produce from the market – INDIAai


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By Anjali Raja K
Earlier, Amazon India had planned to use advanced Computer Vision, ML and AI technologies to manage the quality assurance of fruits, vegetables and other farm produce.
Living in the city, many are worried about the quality of the vegetables and fruits they buy. In addition, the use of pesticides and other chemicals in agriculture are factors of concern. As a result, you might find bruises on an apple or squeeze an avocado at your local supermarket.  
Earlier, Amazon India had planned to use advanced Computer Vision, ML and AI technologies to manage the quality assurance of fruits, vegetables and other farm produce. For example, the model could recognize defects such as cuts and scratches on tomatoes and onions when they have gone wrong. 
The system used a mix of CNN and ViT algorithms. Computer Vision was used to detect cuts, cracks, pressure damage and more. The tech had deployed tomatoes and onions in Amazon stores in India and Europe. They planned to enhance the model to grade the product moving on a conveyor belt automatically.
A model similar to Amazon’s is being developed to detect the freshness of fruits and vegetables. News software can analyze every product aspect before reaching supermarket shelves. It can determine the product’s shelf life and check for internal rot and pesticide residue.  
It integrates sensors and advanced optics into 360-degree cameras that see far more than the human eye. As a result, using the AI model can result in a drastic reduction in food loss. 
One-fifth of all freshly produced products are destroyed before they reach the grocery store. This is because it is poorly handled and stored during transport or decomposes during the journey from farm to retailer.  
The system that processed fruits and vegetables before they were distributed in supermarkets is very old. More often than not, the product is manually sorted on a conveyor belt before being delivered to the retailers. 
A single person inspects 15 to 20 tons of prices per hour by hand. Rapidly sorting more than a hundred tons of produce a day is a time-consuming job. In addition, the workers are at risk of making mistakes and missing defects.  
According to Neolithic’s CEO Amir Adamov, packing houses are the last systematic link to look at the quality before products are read by consumers. However, their analysis is not sufficient. The Neolithic software could observe production and analyze its internal and external aspects. 
The fruit and vegetable supply chain are the most dysfunctional, as produce is the most difficult grocery category to manage. The Herzliya-based company develops software implemented in sorting and automation equipment in warehouses and packing houses. Its AI measures the physical appearance of the product and whether it conforms to the market form, shape and size, as well as its nutritional parameters, including starch, fat, sugar, biomatter and fibre. 
The model searches for anomalies like uneven fluid distribution, which means that even though the fruit looks perfect on the outside, it is spoiled on the inside. The AI also measures residual levels of chemicals and pesticides to check if the fruit is safe to eat.  
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