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Utilizing AI for ‘New Era of Smarter Food Safety’

Artificial intelligence promises enhanced food safety, protecting consumers from poor quality foods or foods that can cause a public health hazard (such as those contaminated with microorganisms). Efficiencies with food processing can be increased by integrating artificial intelligence into the manufacturing processes, according to the website Bio Expert.

The application of digital technology involves the collection and assessment of data drawn from sensors, scanners, and X-rays. The use of artificial intelligence allows the data to be analyzed in real-time. The types of data that help to keep food safe includes temperature, humidity, and other environmental factors can be used together with artificial intelligence to issue alerts and, through the use of automation, to make the corrections.

These technologies are in keeping with the U.S. Food and Drug Administration’s (FDA) “New Era of Smarter Food Safety”, designed to meet the objectives of the Food Safety Modernization Act (FSMA). Here acting FDA Commissioner Dr. Ned Sharpless and Deputy Commissioner for Food Policy and Response Frank Yiannas have outlined how new technologies are central to meeting these aims.

Based on the types of technologies the FDA are interested in, we take a look at three examples of where AI is helping with food safety.

TORMA sorting

An example of the use of sensors comes from TOMRA. The company is a provider of sensor-based food sorting machine, where different technologies like cameras and near-infrared (NIR) sensors, X-rays, fluorescent lighting, and lasers, are deployed. The technology saves time and helps to produce better food quality.

Amazon

Having entered the grocery business through its purchase of Whole Foods, Amazon is keen not to become embroiled in a food safety issue. According to Amazon VP Careltt Ooton, the e-commerce store has begun using Natural Language Processing to scan customer feedback and constantly monitor for food safety issues.

NLP, a subfield of linguistics, computer science, information engineering, and artificial intelligence, is a broad field of computer science that focuses on applying machine learning to understanding language. NLP helps companies to understanding of context, sentiment, and sentence structure, and from this for rapid decisions to be made.

As an example, according to Food Engineering, the following customer complaint was raised with Amazon, where a customer wrote:

“Gave me energy for my workouts, but also wreaked havoc on my digestive tract. That was only taking 1 scoop rather than the recommended 2 scoops. I can’t imagine how sick the full serving would have made me. I had to stop taking it after 3 days.”

The NLP analysis suggested there was an 87.4 percent chance of the issue being a food safety issue. This was sufficiently high for Amazon to pull the product. Subsequent chemical showed the NLP analysis to be correct. However, by not needing to wait for the laboratory data, Amazon avoided more customer complaints and a potential health issue.

Personal hygiene for food processing

Personal hygiene is important during food production and workers need to wear the correct clothing and practice hand sanitisation. In China, the company KanKan developed an application to raise standards for personal hygiene among food workers. The artificial intelligence system uses cameras to monitor workers, making use of facial-recognition and object-recognition software to assess if workers are wearing hats and masks with accuracy of more than 96 percent.

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Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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