An infrared sensor based mobile food scanner will be able to determine the freshness of food. The device can be used by supermarkets and consumers alike to know the shelf life of food item. The technique uses infrared measurements to determine the shelf life and ripeness of a product which will help in understanding the edibility of a food item. Fraunhofer researchers developed the system in partnership with Bavarian ministry of food and the technology is available only for demonstration.

Every year ten million metric tons of food is thrown into garbage according to estimates by the environmental organization WWF Germany. US food and agricultural Association states that the one third of food produced in the world is wasted amounting 1.3 billion tons every year. Developed world which is responsible for the highest amount of food wastes the cost of such waste is US$680 billion.

The wastage is due to numerous factors including food aesthetics, food habits, cultural choices but the major reason is the inability of consumers to determine whether food is edible or not. To address this issue by offering a proactive solution, the Bavarian Ministry of Food launched 17 new initiatives one of which is the Fraunhofer’s food scanner. The device is inexpensive offering the consumer to determine fresh products from farm to table.

In the promising new technology, high-precision infrared beam is shined on the food product, and the reflected light measurement are recorded across the IR spectrum. The absorbed wavelengths will determine the chemical composition of food. The data will be sent to a central cloud where it will be analyzed, and the test results will be sent back to the user’s smartphone app where it will show the shelf life of the food product and consumption span.

Fraunhofer’s researchers have said that the food scanner is only in its initial testing phases and much work remains to be completed. One significant limitation of the technology is that it is only capable of determining freshness of homogenous food products. It is able to determine the freshness of a potato or onion but not that of pizza with many toppings. The research group wants to add new capabilities to the technology by new research. The group wants to employ AI based machine learning algorithms to expand its recognition potential. The more the number of food products tested on the device, through machine learning it will be able to determine and identify complex products.

The research group wants to test the device initially in supermarkets this year to see consumer response. The application can be expanded to other simple homogenous material like such as sorting wool, textiles, minerals and plastics.

Published by Sandali

A former journalist, Sandali is a content marketer with over 5 years of writing experience, across various industries including Food Innovation, Healthcare, and IoT and Technology. Sandali has been weaving corporate stories for organizations through different forms of impactful marketing content. Her key aim is to strategically align well-crafted narratives with business objectives, translating into a powerful communications platform for the company.

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