Artificial intelligence (AI), or machine learning/machine vision, is playing a predominant role in the world of food safety and quality assurance. According to Mordor Intelligence, AI in the food and beverages market is expected to register a CAGR of 28.64 percent, during the forecast period 2018-2023. AI makes it possible for computers to learn from experience, analyze data from both inputs and outputs, and perform most human tasks with an enhanced degree of precision and efficiency. Here’s a brief look at how AI is augmenting food safety and quality initiatives.
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Round the Clock Efficient and Effective Monitoring
Sensors not only monitor temperature, humidity, pressure, and time, but they also record data, highlight areas of improvements, and in some cases, make critical decisions to ensure the safety of the products is not compromised. “Oh, my walk-in refrigerator just texted me,” is a real conversation that most folks in the storage and distribution lines are quite familiar with. Other monitoring techniques include utilizing spectroscopy, lasers, X-rays, or cameras to examine both intrinsic and extrinsic characteristics of produce from harvest to packaging. This is a huge leap from conventional sorting systems that separate what is programmed as “acceptable” from the “rejected” lot, to almost intuitively making decisions based on best yield by sorting products based on their optimized use. Tomra is an example of a business that is demonstrating effective food resource management using machine learning.
Enhanced Traceability with Precision
There used to be a time when the success of a recall or a product trace depended on simply gathering data and interpreting it accurately. Today, executing strategic safety interventions in the event of a recall relies heavily on utilizing the least amount of time possible to gather data, interpret the findings, validate them, and share the results. AI systems have made it possible to compare historical data and predict certain events across multiple timelines from different regions.
When you think food traceability, Amazon is not the most likely name to come to mind. This organization is making headlines through natural language processing—a system that continually monitors and processes customer feedback by scanning millions of emails, instant messages, phone calls, and social media platforms to detect a food safety issue even before the product gets recalled by the manufacturer. At the Global Food Safety Conference 2018, Carletta Ooton, vice president of health and safety, sustainability, security, and compliance at Amazon, shared how the leading digital retailer blocks a faulty product on an average of 50 days before the official recall, simply based on collective customer feedback.| | | Next → | Single Page
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About Judy Sebastian
Judy Sebastian, Food Quality & Safety's blogger, has a dual specialization in public health and safety and organizational development. Equipped with over 10 years of experience in food safety systems implementation, workplace culture assessments, and talent development strategies, she is passionate about global food culture and how it impacts our daily lives. Judy is a certified trainer and consultant with Dubai-based consultancy Apex Food Consultants and is currently based in Portland, Ore. Reach her at email@example.com.