Smart Food

4 min readMay 8, 2022

By Sanjana Mishra, Computer Science, 2023

Whether it’s dining at your favorite restaurant or making a bowl of cereal, food is something that connects everyone. But what connects us to our farmers? The entire food industry is built on the need to transport products from our farms to our fridges and then into our stomachs. As of right now, manufacturing, distribution and retail account for a little under half of edible food waste. Essentially, the food processing and handling industry is horribly disorganized and it’s leading to an exorbitant amount of waste. So how do we make processes like this more efficient? The answer lies in artificial intelligence.

Artificial intelligence (AI) has the potential to revolutionize this aspect of the food industry as we know it today. While automation has become more prevalent in all aspects of the industry, AI takes this a step further by introducing “smart” software. This software can essentially do what humans can do — recognize food, determine quality, etc — by using sensors, robots and other kinds of information gathering techniques. From the raw ingredients to the fully prepped meal, AI can help increase efficiency, yield, and consumer satisfaction while also helping corporations maintain superior quality.

At its most basic level, AI can aid the food processing and handling industry by boosting and sustaining customer satisfaction. One way of doing this is by making transportation of food items more efficient and organized. AI can improve the current transportation process by consolidating data about a product as it travels from farm to consumer — making the tracking process much simpler. This benefits customer satisfaction as it increases transparency as well as possibly preventing surplus.

Additionally, AI can make testing a product at every stage of the supply chain simple — a goal that is time and labor intensive with the technology available to us today. AI implemented through automatic testing and sensor checks can make this testing process simpler — again improving consumer satisfaction. This kind of quality control and contamination prevention are two important aspects of food processing and handling, and corporations are already working on improving the process. TOMRA, a sorting and collection solutions provider in Norway, is using x-ray, near infra-red spectroscopy, laser, cameras and a machine learning algorithm to examine the different features of the objects they’re sorting. Essentially, this machine can help ensure that the best quality produce and food items are going to market. TOMRA can pick out unripe, bruised, or bad quality fruit, ensuring that the food company’s reputation remains positive; and, in the rare case an orange finds itself in a barrel of apples, TOMRA can put it back where it belongs. TOMRA’s goal is to ensure product safety while also making the process of sorting foods more efficient and convenient. This can help food companies prevent huge recalls which cost time, revenue, and additional resources while also damaging a brand. Corporations and agencies can use services like the ones TOMRA provides in order to increase yield and revenues, as well as efficiency.

While TOMRA’s algorithm directs the machines, the machines themselves need to be cleaned in order to prevent contamination — this is where AI comes in again. The University of Nottingham developed the Self-Optimizing-Clean-In-Place (SOCIP) which uses optical fluorescence imaging and ultrasonic sensing technologies to collect data and share it with a machine learning algorithm. This algorithm can monitor microbial debris and food particles present in the machines. By implementing this technology, the University hopes to help food companies in the United Kingdom save 133 million pounds a year while cutting equipment cleaning time in half.

At a higher level, AI is used in a more controversial manner: to ensure that basic hygiene is maintained by restaurant employees. In Shanghai, China, the municipal health agency implemented AI enabled cameras in hundreds of restaurants with the goal of helping managers make sure that their employees are following health codes. If a possible violation is detected, the image is extracted and then sent to a manager for investigation purposes — helping prevent contamination and also maintaining a high standard of quality assurance.

Artificial intelligence is the future of computer science, and many other industries — including our food. By working on speech and visual perception, decision making, translation, and more “human-like” skills, computers may be able to solve the problems of the future — like how to make sure the ripest avocado ends up on your kitchen table.

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Smart Food

Written by Sanjana Mishra