I would like to declare at the very start of this article that this might not completely be a food science article. So, apologies to all this weekend, for deviating a bit on this Food Science blog. However, this is one topic I have been meaning to write for a very long time, and voila! Here it is.
Before coming to Artificial Intelligence in the Food Industry let’s take a quick read into Artificial Intelligence (AI) in general. Have you seen the movie ‘The Imitation Game’? If not, please do watch it. The movie runs around a central question - Can machines think? Well, that and the war. AI very often runs parallel with the task of cognitive thinking. Artificial Intelligence means that machines can function and think as humans, learn from previous experiences, and have a large data center. In the present world, AI has reached the stage of being able to play chess, self-driving cars, and much more.
AI has also now entered the segment of the Food Industry. From managing supply chains to restaurant orders, many new-found applications exist in the industry. The industry is soaring, and so is the vast expanse of opportunities that are being created along with it. AI will increase efficient ways to produce food for a vastly growing population. Although the Food Industry began with a sparse adoption of technology, today AI is gaining new heights in the business due to the below-mentioned reasons.
Improved product quality : Visual inspection and comparing the vision to the input specifications has greatly been a boon to the industry. This all being done in quick time is an added benefit. Packaging fill levels and label placement are few such examples where AI has helped. Root cause identification is another such instance.
Greater maintenance efficiency : Maintenance issues and breakdown time are real issues in any industry. Predictive maintenance rather than corrective maintenance greatly reduces the cost of maintenance. Sensors and previous breakdown data might help to predict breakdown. Any small changes in machines might be sensed by these sensors warning the personnel of an occurring breakdown. This might also reduce any wastage that might occur because of breakdown.
Insight from data : Data science and analysis from a huge range of data might give insights that are worth acting on. Actions that might reduce wastage, reduce processing time, reduce downtime, increase yield/efficiency, and in total reduce the cost of processing and add value to the product.
MNCs as well as restaurant chains have begun to incorporate AI into their farm to fork chains. Farmers working to harvest their products are making use of AI for better prediction. The main sectors where AI is finding its application is sorting of food products and packaging, ensuring personal hygiene, management of supply chains, New product development, cleaning of equipment, and farming practices (read more at https://foodindustryexecutive.com/2018/04/6-examples-of-artificial-intelligence-in-the-food-industry/).
AI will provide areas of improvement in the industry, reduce risks and costs. However, the humans of the Food Industry will never be replaced completely as humans will oversee the operations and bring new ideas and innovations to the table. The optimal way to move forward would be for AI and humans to move hand in hand which will allow the Food Industry to attain new heights of innovation.
SOCIP (Self Optimizing Clean in Place), being developed by the University of Nottingham works with optical fluorescence imaging and ultrasonic sensing, measuring the food residue and microbial debris in equipment. This would reduce over cleaning of lines and the costs involved in conventional CIP. Gastrograph AI is predicting how their target audience is going to respond to their flavors and products. KanKan is a company that is working on AI that checks personal hygiene. The camera uses facial recognition to screen wearing masks and hats. If any non-compliance is found, screen images are taken. Coca-cola used the idea of self-serving soda fountains to allow its customers to produce their personalized drinks. With the help of data collected, it found out the most popular drink made and released a new product into the market ‘Cherry Sprite’.
Gobble, has introduced dinner kits that can be assembled in 10 minutes. It uses data science to predict the changing tastes and preferences of customers and acquire its supplies. Restaurants can make optimum use of AI. Applications like Zomato and Swiggy exist for us at the touch of our finger. Food selling sites and applications, voice-searches for placing an order, self-serving systems, robotics, restaurant revenue predictions, and machine learning are some mind-boggling innovations in the food industry.
Photo by: www.flewup.com
What can be concluded is that we have just touched the tip of the iceberg and there is a lot of room for new opportunities in this area.
References:
1. Artificial Intelligence, What is it and why it matters, www.sas.com
2. 6 Examples of Artificial Intelligence in the Food Industry, www.foodindustryexecutive.com
3. How Artificial Intelligence is Revolutionizing Food Processing Business? , www.towardsdatascience.com
4. Machine Learning and AI in Food Industry: Solutions and Potential, www.spdgroup.com
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