Food goes the AI way — see top applications of AI in food industry

The future of economies is dependent on Artificial Intelligence (AI) and it is billed as catalyst for developing and developed economies. The market for AI is expected to grow to $5.05 billion by 2020. While every industrial sector is taking note of this massive opportunity, the food industry is also playing catch up in this sphere. Food and beverage industries can leverage AI to improve offerings, optimize operations, and deliver a better customer experience.

Reports suggest that 77 percent of millennials dwelling in UK/US would want to use AI technology to obtain better assistance in planning and cooking healthy meals. Besides, the overall cost of implementing AI-based solutions is lowering. Thus, brands can tap into a myriad of opportunities that AI presents.

US-based RND64 has developed an AI-powered ‘home-cooking sidekick,’ named Hello Egg. The AI powered product, showcased at CES 2017 will empower millennials to eat healthier. The home assistant is controlled through voice technology, and utilizes AI to address any kitchen needs. Besides, the device can plan weekly meals according to dietary preferences, demonstrate cooking tutorials on its convex video screen, supervise the pantry, organize shopping lists, and arrange grocery delivery.

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AI driving consumer engagement in food sector

1) Enterprises are leveraging speech and image recognition for time optimization and consumer engagement: Lark is one popular application that acts as a personal diet coach, and utilizes speech recognition to log meals. Users have to simply voice log what they have eaten on the app, so that it can estimate the amount of calorie intake, besides furnishing personalized nutritional advice. Lark provides a simple instance of how AI can be leveraged for food industry. Nutritionix Track is another similar voice-activated apps showing promise.

Google doesn’t plan to stay behind in this race of transforming food industry using AI. Google’s Im2Calories helps user estimate the nutritional content of a meal from a photo. The product makes extensive use of image recognition technique to achieve this.

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2) Businesses are increasingly relying on NLP and machine learning techniques to obtain more personalized products and advice: With the help of NLP and machine learning, enterprises can process data much better. Let’s consider the case study of a data-rich fitness tracking app, called Lifesum. The firm leveraged AI to address a local health issue, and design a custom-made product for its users.

After thorough analysis, Lifesum found out that London consumers were suffering from fatigue and stress due to insufficient levels of vitamin E, zinc and omega-3 in their diet. The company created better products and new business opportunities,  by implementing AI-based technologies, which provide better data insights.

3) Using AI based chatbots to increase user engagement: When chatbots are augmented with AI, they can provide responsive and cost-effective customer service to a limitless audience over messaging platforms. Whole Foods designed a chatbot for Facebook Messenger. The chatbot displays products and recipes based on special diets or specific ingredients and cuisines to their consumers.

Just Eat and The Guardian’s Sous-Chef also furnish similar offerings. Thus, chatbot development is good strategy to kickstart a venture in the food industry, i.e., if AI is your base technology.

AI  streamlining food industry

1) The Sorting system: Reports suggest that AI will introduce profound changes for the fast-moving consumer goods industry, which includes processed and fast food markets. These changes could mean improvements in the production line. AI shall incorporate the use of smarter machines, thus assisting towards minimizing or eliminating food waste.

TOMRA branded Sorter uses AI

TOMRA is an organization that makes sorting machines, which leverage AI. For instance, potatoes deemed too small are not ideal for fries. This is not all, consumers usually tend to discard the fries which appear too long, too small, or thin.

This is where TOMRA’s AI-based food sorting machines come in. The intelligent machine could help in data detailing the minimum standard of quality the fries must have. These AI machines can also sort potatoes into those set for French fry production, or those better suited to crisp or potato wedge products.

2) Fast food can be delivered swiftly using AI: The technology will put many low-skilled workers at food establishments out of work, as it can impressively automate simple cooking, for say, making a burger.

US-based Momentum Machines is on the road to eliminate need for fast food burger cooks. The organization built a 24-square foot machine-powered burger assembly, capable of creating 400 burgers an hour. Moreover, speed is an essential element fast food joints focus on improving. Such a solution not only saves hundreds of thousands in worker wages, but also ensures swiftness in delivery.

3) Addressing cleanliness using AI: All facets of the food industry can be improved using AI. This can be illustrated with University of Nottingham’s artificially intelligent sensor system, designed for cleaning of food manufacturing equipment, which currently accounts for 30% of energy and water use in the sector.

AI can be utilized for optimizing the equipment cleaning, which will enable the university to save £100m a year. The university is assessing the potential of using an artificially intelligent inspection system, aiming to reduce cleaning times and resources by 20%-40%. Furthermore, this system will be equipped with ultrasonic and optical sensors.

Last Word

AI will intersect with effective data analysis techniques to offer efficiency, broader reach, advanced recommendations, new product development, and better consumer engagement. It could mean profound transformations for players in the food and beverage industry.

News reports suggest that food manufacturing industry is set to be one of the most affected sectors with the implementation of AI technologies. Globally, many companies and startups are venturing in this direction. It’s about time for India to join the race, and make best of the initial wave. According to reports, early adopters of AI across the food industry can expect revenue increases of 39% by 2020, while still retaining or retraining 80% of their existing employees.

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by Vijayalakshmi Anandan

The Deep Learning Curve is a technology-based podcast hosted by Vijayalakshmi Anandan - Video Presenter and Podcaster at Analytics India Magazine. This podcast is the narrator's journey of curiosity and discovery in the world of technology.

Amit Paul Chowdhury
With a background in Engineering, Amit has assumed the mantle of content analyst at Analytics India Magazine. An audiophile most of the times, with a soul consumed by wanderlust, he strives ahead in the disruptive technology space. In other life, he would invest his time into comics, football, and movies.

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