How the Food and Beverage Industry is Affected by Machine Learning and AI
Guest WriterGuest Writer
In general, when thinking about the food industry, we are likely to think about customer service and takeaway gig-economy services. More recently, the COVID-19 pandemic and how it ties into making or breaking food businesses are at the forefront. Perhaps one of the last things to come to mind when discussing the food industry is modern technology, especially artificial intelligence, and machine learning. However, these technologies have a massive impact on the food and drink industry, and today we’re going to explore how.
Whether you’re looking at the food or the industry's beverage side, every aspect of the process is impacted by machine learning or AI. Hygiene is a massive and important part of the food industry process, specifically when minimizing cross-contamination and maintaining high standards during a pandemic.
AI and Machine Learning are significantly impacting the food and beverage industry, including the manufacturing process, during the COVID-19 pandemic.
In the past, these tasks would be tedious, time and resource-intensive, and potentially expensive if a mistake was made or overlooked. In large manufacturing plants, complex machines would actually need to be disassembled and then put back together for them to be cleaned properly and pumping a large volume of substances through them.
However, with modern technology, this is no longer the case.
Using a technology known as SOCIP, or Self-Cleaning-in-Place, machines can use powerful ultrasonic sensors and fluorescence optical imaging to track food remains on machinery, as well as microbial debris of the equipment, meaning machines only need to be cleaned when they need to, and only in the parts that need cleaning. While this is a new technology and the current problem of overcleaning, it will still save the UK food industry alone around 100 million pounds a year.
Of course, the food and drink industry's waste aspect is a highly debated and criticized part of the industry. The foodservice industry in the UK alone loses around £2.4 billion in wasted food alone, so it’s only natural that technology is being used to save this money.
Throughout the world's supply chains, AI is being used to track every single stage of the manufacturing and supply chain process, such as tracking prices, managing inventory stock levels, and even countries of origin.
Solutions that already exist, such as Symphony Retail AI, uses this information to track transportation costs accurately, all pricing mentioned above, and inventory levels to estimate how much food is needed and where to minimize the waste produced.
No matter where you go in the world, food safety standards are always important to follow, and regulations seem to be becoming stricter all the time. In the US, the Food Safety Modernization Act ensures this happens, especially with COVID-19, and countries become more aware of how contaminated food can be.
Fortunately, robots that use AI and machine learning can handle and process food, basically eliminating the chances that contamination can take place through touch. Robots and machinery cannot transmit diseases and such in a way that humans can, thus minimizing the risk of it becoming a problem.
Even in food testing facilities, robot solutions, such as Next Generation Sequencing, a DNA testing solution for food data capturing, and Electric Noses, a machine solution that tests and records the odors of food, are being used in place for humans for more accurate results. At the time of writing, it’s estimated that around 30% of the food industry currently works with AI and Machine Learning in this way, although this number is set to grow over the coming years.
There’s no doubt that food production uses a ton of water and resources, especially in the meat and livestock industries. This is extremely unsustainable for the planet and very expensive for the producers. To help curb costs and become more sustainable, AI is being used to manage the power and water consumption needed, thus making it as accurate as possible.
This creates instant benefits to the costs of production and profit margins in all areas of the food and drink sector. When you start adding the ability to manage light sources, food for plants and ingredients, and basically introducing a ‘smart’ way to grow food at its core, then you really start to see better food, more sustainable production practices, and more profits and savings at each stage of the food chain.
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