The food industry is already reaping the benefits of artificial intelligence. But the development is still in full swing. Numerous projects are being supported by the scientific community. These projects are opening up new perspectives and removing obstacles on the path to efficient food production and delivery. One thing that all projects have in common is that the use of AI optimizes the entire process and prevents food waste.
Avoidance of overproduction
It is a well-known problem that every year, several million tons of food are thrown away in Germany alone. But how can overproduction and waste be reduced in the baked goods, dairy and meat products sectors? The funding project REIF launched by the Augsburg University of Applied Sciences has set itself the goal of discovering and combating waste along the food chain. And in doing so, it focuses on machine learning.
Artificial intelligence can help provide accurate consumer demand forecasts, even in the short term.
These forecasts enable the food industry to align production structures and logistics more efficiently.
The key to solving the problem of overproduction and oversupply is to forecast fluctuating demand as reliably as possible. Food companies prefer producing too much rather than too little when in doubt. After all, economically speaking, empty shelves are more dangerous than unnecessary deliveries.
AI helps reveal the correlations between demand and other factors that would otherwise remain hidden. For instance, seasonal or weather-related influences that affect the demand for certain foods. Artificial intelligence is able to track down even previously undiscovered correlations – and draw the right conclusions.
What is food-relevant data worth? Quite a lot. Especially when this information is used for tangible forecasts by means of artificial intelligence. These forecasts accomplish more than just helping the food industry to optimize production. Finance and insurance groups operating in the global market for raw materials and food also benefit from them.
The project EVAREST aims to build a platform that makes all these data available. The German Research Center for Artificial Intelligence (DFKI), the CISPA Helmholtz Center and Saarland University are working on this project together.
With AI an immense amount of relevant data is collected and analyzed:
Raw materials that are important for food production,
supply chains and transport routes,
development of demand.
Linking this information optimizes food supply efficiency at every point in the production and supply chain. It goes without saying that this data and its professional analysis will become a highly sought-after commodity.
Food online – ecologically correct thanks to AI
Online trade is booming – but when it comes to groceries, most consumers still rely on the supermarket around the corner. There is no question that ordering groceries online – without first actually holding them in your hand — calls for a high level of trust on the part of the consumer. In addition, the additional transport routes involved in online shipping are ecologically questionable. But artificial intelligence can also be helpful in these areas.
It is well known that artificial intelligence plays an increasingly important role in logistics. AI shortens delivery routes and delivery times by providing tools that react in real time to the respective traffic situation. To do this, AI optimizes the relationship between warehouse and demand locations and reduces resource consumption in the supply chain. Avoiding traffic jams and overly long delivery distances makes the supply of food to the front door (or at nearby pickup points) more ecologically efficient and, through shorter delivery times, also more convenient for the consumer.
Food tools for the consumer
This might be an everyday situation: A look in the refrigerator leaves you wondering
Which foods are still fresh?
And what tasty dishes can I cook with what I have in my refrigerator — and without having to buy new food?
More and better information about every single food item helps consumers reduce food waste. The project Fresh Analytics is working on exactly this problem. Five cooperation partners are developing solutions for the collection and analysis of complex food-relevant data. These could, for example, serve as the basis for simple apps that identify what is still edible, and create menu suggestions based on the current contents of the refrigerator.
Another possibility that arises from this database is the use of dynamic price models that allow retailers to react flexibly and promptly to expiry dates. Access to shelf-life and other relevant food data creates added value for retailers, consumers and the environment.
Economy or ecology? AI resolves contradictions
Thanks to the intelligent analysis of data, the development of the food industry is headed for a sustainable future. Let us hope that all of those involved in this process will recognize the advantages of AI and use them throughout the entire sector — from the procurement of raw materials and production, to distribution and the behavior of the end consumer. AI therefore simultaneously achieves two goals in the food sector: it increases economic efficiency and ensures a more ecological food supply.
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