How IoT and AI can Impact the Food Industry?

CIO Applications| Wednesday, December 16, 2020

Customized AI-assisted cooking helps people prepare their meals in the required portions, having a significant effect on eliminating food waste to a greater degree.

Fremont, CA: While innovations have proven to be beneficial for a variety of industries, they can also help the government and other stakeholders to resolve the issue of food waste. IoT and Artificial Intelligence are two innovations of this type that can be of significant use here. However, before contemplating the introduction of any emerging innovations, adopters should be well aware of possible use cases where technology can add value. But for this to happen, there is a strong need for in-depth understanding and awareness of how technology work and can benefit. Therefore, adopters should have a fair knowledge of how these technologies can be beneficial before adopting IoT and AI to minimize food waste.

Here are two areas where IoT and AI can influence the food industry.

IoT to Decrease Food Waste

IoT will contribute to the development process. Food producers may not be aware of this, but an immense amount of food is lost during the food processing process. As the stage of food production includes heavy-duty machinery, the risk of equipment causing crop damage is high. Some of the other considerations include spilling, handling, and storage. To solve this dilemma, the first step is to define the real causes of food waste. And for this, it is mandatory to monitor food waste in real-time. Real-time farm data can be obtained by embedding several sensors and cameras on the field. Using these sensors, farmers can monitor exactly where food is being wasted and take adequate steps to minimize food waste. Food waste can be controlled not only by farmers but also by government officials.

AI to Decrease Food Waste

A grocery store with a wide variety of food products must be replenished whenever the need arises. If the stock is filled before food products are still unsold, the risks of pest attacks are higher. One of the many explanations for this is the insufficient tracking and prediction of food stocks. Instead of using manual processes, using AI will make this process fast and effective. AI tools can develop accurate forecasts by entering historical data about food stores, previously wasted food, and real-time shelf information. Dealers may thus obtain a better understanding of when a specific food item is out of stock. With accurate details, retailers can then order only the appropriate quantity of food products.

Another common explanation for food waste is inadequate and inefficient management of the food supply chain. Many times, without testing the food quality, the food is packaged and shipped to retailers. Retailers, without knowing this problem, are packing their shelves with low-quality items. There is a high risk of such food being wasted. To avoid such waste, food producers are working on an AI-powered food inspection system that tests food quality before it enters the consumer's hands. Some systems can independently track, evaluate, and determine the quality of food. The AI, ML, and DL components learn and perceive secret patterns that may not be apparent to the human eye. If a specific food is about to rot faster, producers will first send this stock to the distribution centers.

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