Source | www-forbes-com.cdn.ampproject.org | Ilker Koksal
When talking about food quality, AI isn’t usually the first thing that comes to mind. But by integrating AI into the food manufacturing process, companies can maximize efficiency in quality control. According to Mordor Intelligence, artificial intelligence in the food and beverage market was valued at $3.07 billion in 2020 and is expected to reach $29.94 billion by 2026 at a CAGR of over 45.77% during the forecast period of 2021 – 2026.
One of the pillars of food quality is the safety of the food. Reducing the presence of pathogens and detecting toxins in food production is a key part of AI. Japanese company Fujitsu has developed an AI-based model which is used to monitor hand washing in kitchens with six-step hand washing regulations set by the Japanese health ministry. Fujitsu’s model builds on its existing behavioral analytics capabilities, which can already recognize a variety of subtle and complex human movements using deep learning techniques without relying on large amounts of training data. The technology captures images of complex handwashing movements as a combination of hand shape and repetitive rubbing motions, using two deep learning engines: hand shape recognition and motion recognition. With a handwash video dataset comprising about 2,000 variations of people, camera positions, and soap types, Fujitsu said its technology was able to detect the six-step hand washing process with an accuracy rate of over 95%. Using AI in this part will definitely reduce the need for visual checks where food safety must be increased, especially in the COVID-19 process