Artificial Intelligence Applications In Food Industry

Did you know that the world population is projected to escalate to about 9 Billion by 2050? To feed this vast number of people, the agriculture sector would need to increase its productivity by about 70%. To successfully achieve this, technology will need to be a core unit in the food industry.

Artificial Intelligence has a vital role to play in future food production. Food and beverage companies are moving fast using technology for operations and logistic efficiencies and onto how to meet consumer desires. The prominent players in the industry have embraced Artificial Intelligence to maintain strong empathy with their audience.

Hi everyone! This is Mert Damlapinar, and in this video, I'll show you various applications of Artificial Intelligence in the food industry along with its drawbacks and the solutions to these challenges.

 AI In The Food & Beverage Industry

AI is transforming several sectors, including government, medicine, advert, and finance, to name a few have adopted this technology. By learning the intricacies involved with big data analytics and AI, the food and beverage industry has begun utilizing the numerous predictive analysis applications offered by this technology.

An interesting fact we discovered is that the global AI market in food and beverage companies is estimated to grow annually at a compound growth rate of 42% before 2021. This has become evident by the increasing amount of food companies that are using Artificial Intelligence to generate more revenue and improve their productivity.

Various Applications of AI In the Food Industry

For the first time, the light of technology has dawned dramatically on the food industry and has been implemented without any hesitation. AI is now known to be impacting many aspects of the industry, such as financials, production, distribution, marketing, consumption, packaging, and storage.

To give a better explanation of the extensive usage of Artificial Intelligence in food manufacturing, processing, and distribution, here are a few notable highlights:

• Sorting

Sorting food requires that extra attention is paid to the specific details of the product, for example, size or color. These factors help food companies to make well-guided decisions on the processing of various foods that will ultimately increase the purchase rate of consumers.

Companies in the food industry, such as TOMRA Sorting Food are among the few that take advantage of AI to develop machines that significantly improve the sorting of food. These technology-inclined systems are sensor-based and use features such as cameras and near-infrared sensors to visualize food products with human perception.

• Implementation of personal hygiene habits by employees

We know that the importance of ensuring that employees in food and beverage companies take necessary personal hygiene precautionary measures cannot be overstated. AI enables companies to quickly detect any inefficiencies in this aspect and eliminate them for improved food safety.

You must have noticed several CCTV cameras installed within restaurants. Sounds familiar, right? This is an advanced AI system technology that involves the use of special cameras equipped with facial recognition and object recognition features to ascertain if workers are committed to keeping the laws of food safety.

• Reducing equipment repair and maintenance costs

Any professional in the food industry knows how much of their company's resources go into cleaning processing machines and also repairing them. Ongoing research projects suggest that a system known as the Self-Optimizing-Clear-In-Place (SOCIP) which can improve cleaning time and drastically reduce resources used for cleaning, including water.

This Artificial Intelligence technology uses features like ultrasonic sensing and optical fluorescence imaging to detect the tiniest amount of food leftover and microbial debris present in the equipment. This aids in the optimization of the cleaning/maintenance process.

Companies can also utilize AI in the aspect of machine repair and periodic optimal functioning check. It can quickly detect any piece of equipment that’s faulty and separate them for immediate replacement of its degraded components. This will ultimately lead to improved employee efficiency and human resource management as there’s a much better system in place to provide early detection of any fault.

• Optimized supply chain management

The food industry can use Artificial Intelligence to minimize delays and maximize profit margins by providing close monitoring of every supply chain operation. This also helps companies to forecast for better management of pricing and stock products accurately.

With growing concerns about transparency, Artificial Intelligence has also been utilized to track products from the farm to consumers to ensure transparency. You can be sure that the flow of products will be cost-effective and streamlined in the best way possible with the adoption of this technique into food production and distribution.

• Revolutionizing the whole in-store shopping experience with new products

Based on the available demographic data and statistics available, many food companies have been able to provide location-specific varieties of food flavor combinations that are targeted at a preferred group of consumers.

By closely monitoring conversations on social media and using unique algorithms, companies can use AI to analyze consumer data and identify sentiments or behavior that are crucial, not only in building positive experiences but also in the development and design of new product lines.

This has proven to be an immense contribution to the food industry because companies can now offer unlimited forms of flavor combos, spices, and ingredients.

• Personalized customer service

We noticed that consumers prefer a more personalized experience as they shop. Using chat boxes or voice assistant powered by natural language processing, companies can tap consumer shopping data and history to provide a hyper-personalized and automated customer service experience.

Using these predictive analysis technology provided by AI solution providers, food companies can monitor what decisions customers do overtime and what food they always re-order. This ensures that the consumers are provided with a personalized feed containing their preferred food options.

• Better farming conditions

Have you ever imagined how heartwarming it would be if there was a way farmers could cultivate better food under optimal growth factors? Well, it may surprise you to know that companies are have already begun to research how they can apply this feature of Artificial Intelligence technology to better suit the farmers.

Worthy of mention here is a company known as Sentinent which aims to invent a system that can create growing conditions where the effects of factors like light intensity, temperature, salinity and water stress on basil can be carefully checked.

As of yet, progress is only being made in the lab with all available data. They are looking to come up with specific "ingredients" for making perfect foods.

Modern applications of artificial intelligence in the food sector include achieving significant reductions in the downtime, reducing consumer friction at the point of sale, speed up of manual tasks, and improving worker-overtime ratio to name a few.

Challenges Of AI and Available Solutions

So, with all the diverse ways listed above on how AI is improving the food industry, it might hit you like a ton of bricks to hear that this amazing technology has also got its cons. While there are many benefits, there are just as many challenges.

Companies have to decide whether to buy or build this technology and ideally, food companies would develop their own unique in-house technology systems. However, to be pragmatic, a lot goes into acquiring these systems. Some of the challenges that come along with using AI in the food industry include:

Cost: Potential adapters face numerous difficulties with the price being the biggest among them and getting buy-in for these type of tech systems.

Integration issues: It's never easy to integrate new technologies. This also works similarly for the integration of AI in food companies. If you have a plan sticking and adapting to it will play a significant role in this.

Proprietary data: With the right proprietary data, food and beverage companies may not be able to build artificial learning models that can perform.

Given the above fundamental challenges, we'll provide two solution ideas, especially for large companies with much capital that can be invested in adopting AI technology.

 ·        Food companies that have already established data analytics and a team of professional developers can go on to safely build their own AI platform. You don't want to jump into making this decision if your company's team of developers lacks the required competency to match up with the in-house AI system.

·         They should be skilled enough to keep this system always updated to avoid any future troubles.

·         Various companies that lack such resources should find food and beverage solution providers that have already established AI systems which will improve the front-end and back-end processes in your company.

·        A few examples of these solution providers are SAP and Bundled Solutions Built for Food & Beverage Distributors.

75% of millennials in the US, and the UK would want to use AI technology to obtain better assistance in planning and cooking healthy meals. AI is growing at a rapid pace, and we've witnessed more companies within the food and beverage industry that are investing in AI solutions for better performance. 

The predictive analysis provided by this cutting-edge tech is being used to resolve various critical problems in this industry. What's more? A lot of these companies have gone a step ahead to combine other areas of AI with predictive quality analytics to create new opportunities to develop more potential products for the future.

So, next time you decide to order some food from an online grocery store, consider thinking of the predictive ability of some of the already implemented AI systems.

You can also watch the full video of this article here:

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