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The food supply chain is one of those things you hardly ever think about -- until there's a shortage of the products you need.
The recent global pandemic has highlighted the criticality of the food and goods supply chains. What we might have once thought of as limitless' can quickly turn out to be critically short in availability when supply chains are upended.
Fortunately, machine learning and AI are replacing outdated ways of planning and forecasting with more intelligent methods. By making the predictions more adaptable, AI can ease the worry when it comes to the food supply. Let's look at some of the advantages of AI in agriculture.
Improved forecasting and planning with machine learning
One of the primary challenges with any supply chain is the ability to forecast the expected demand for a product ahead of time. For example, if it takes six months to grow and harvest a particular acre of crops, knowing how many will be required would avoid overproduction or undersupply of necessary items.
Traditionally, production-oriented companies have used formulas, spreadsheets and even intuition and experience to know how much to produce of a given product and where the right places were to ship those products to meet expected demand. Unfortunately, the rapid shift from traditional work and living patterns to the current work-from-home and quarantine lifestyle has dramatically shifted supply chains.
In the first few weeks of the pandemic, chronic shortfalls in goods ranging from toilet paper to baking yeast continued to dog supply chains. Organizations that have relied on tried-and-true spreadsheets, formulas, rules-of-thumb and experience are having to turn to different approaches.
Companies are using the power of big data and machine learning to spot trends and, perhaps more importantly, anomalies in purchasing or consumption behavior. While it is not possible to harvest crops that have not already grown or manufacture goods on short notice that require months to assemble, AI-based machine learning systems can provide an early warning when patterns change.
Machine learning is particularly strong with predictive analytics and pattern matching, two of the core seven patterns of AI applications. Supply chain managers and production teams can add the power of intelligent predictions to their existing toolboxes by using data-driven machine learning systems to discover if adjustments are needed.
Increased productivity and yield in AI-enabled farming and food preparation
Beyond simply providing greater insight and visibility into supply chains, AI is helping to optimize food production and preparation. As of 2019, more than $852 million is being invested in AI in agriculture systems, according to a report by Prescient and Scientific Research.
The areas of investment include automated and autonomous farming operations, AI-enabled production and yield management along with AI-enhanced picking, packing and sorting. It is through these processes that AI hastens food production, development and delivery.
AI-enhanced robots, drones and farm equipment are being used to assist with the preparation and harvesting of food. Sensors in drones are being used to more accurately target irrigation, weed control and crop management. Autonomous picking machines are helping to deal with a shortfall in farm labor and to increase overall efficiency.
AI-enabled computer vision systems can inspect goods and make sorting operations more efficient. AI systems are even being used in meat packing and butcher applications.
Any number of problems can occur with crops and soil, from soil poisoning to pests, to poor soil health. AI is being deployed at agriculture locations to help detect these issues as early as possible to limit and prevent any damage.
A machine learning-enabled system known as the Nutrition Early Warning System is designed to analyze regions to predict food shortages. The system is currently able to detect risks such as droughts, rising food prices and crop failure.
Greater food safety in storage, compliance and auditing
Proper storage of products in the food industry can be difficult, as requirements vary. Being able to sort everything into the proper storage location is time-consuming, as well as costly, and is often done manually.
Food producers are increasingly using AI to sort products into the right storage locations and to reduce the amount of human involvement needed. Not only can machines sort faster than humans but, combined with the power of machine learning and AI, many of them can sort more accurately than their human counterparts.
These systems are also helping with food safety by tracking supplies with the help of cameras. They can follow the movement of foods and check whether staff are wearing the proper safety apparel. This enables staff to analyze trends, find out if there have been violations and better protect the public.
AI can also help companies determine if their equipment is clean and the optimal time to perform the cleaning. Some cleaning equipment such as vacuums and sanitization can even help automate cleaning. One group of researchers from the University of Nottingham estimated that their AI food cleaning technology can save $133 million a year in the United Kingdom alone.
The increasing application of AI in our food supply chains
As of 2019, the European Union has more than 30,000 robots working in its food industries. These robots, powered by AI, are making food supply chains safer and more efficient. The result is less food waste, which can reduce the overall cost of food and help ensure that we have the right amount of food available to fill demand.
There are two major concerns about the involvement of AI in the food industry and the answers to them are intertwined. The first concern is that AI will start replacing workers and put people out of jobs. Second, people are worried about the safety of involving AI in controlling our food supplies.
AI is seen by many professionals as a technology that will never eliminate the necessity of humans. Jobs will be lost in some areas, for example food supply sorters, but created in others. One example of those jobs includes safety inspectors who will have to make sure all AI is functioning properly, and that equipment is both clean and safe. Programmers, supervisors and similar roles will be needed with the further implementation of AI into the world of the food industry.
With the world changing at an ever-increasing pace and in unpredictable ways, people continue to seek safety in their homes and other areas of comfort. No doubt the food supply chain is critical to keeping society functioning and stable. As a result, there's no doubt that we will continue to see the increased application of AI and machine learning in our food supply chains.