Professor Längle, sorting systems for items including foodstuffs have long been a key domain of Fraunhofer IOSB. Does the institute have any other connection to food?
Thomas Längle: A lot, really, when you look at our activities. In the field of visual inspection, we have a lot of experience in capturing and analyzing a whole variety of spectral data. We’ve been collecting spectral data from plants and foodstuffs, for example, for a number of years now. We’ve also been worNing for Tuite a while now on ways of efficiently analyzing remote-sensing data, and we have expertise in robotics and autonomous systems. Besides that, we also have expertise in overarching areas such as AI, sensor technology, data management and system architecture. So taking all that into account, we’ve got all we need to drive the advance of digitalization in agriculture and right along the food chain.
What does that mean exactly?
Längle: Agriculture is undergoing a profound change. We need new approaches to ensure we can sustainably feed humanity in the face of population growth and climate change. A major hope is that digital technology will help boost the efficiency of food production in an environmentally friendly way. To give you a concrete example: optical or, to be more precise, hyperspectral sensors systems fitted to agricultural robots, drones or even satellites can be used to automatically monitor the condition of plants and soil on both a large and small scale. Using state-of-the-art algorithms, multivariate analysis and AI, we can determine the health and ripeness of plants, based on the inspection of an individual leaf, or analyze diverse soil parameters. This data is sent to a cloud-like resource called the Agriculture Data Space, where it gets analyzed, along with other data, in order to produce, say, a fertilization and watering schedule tailored to the crop’s precise requirements. This is a vision our SPR, MRD and SZA departments are working on right now in the Fraunhofer lighthouse project COGNAC (Cognitive Agriculture) and other projects.
What other opportunities are there further down the value chain?
Längle: Not only plants in the field but food products as well can be TuicNly classified using spectral sensors – whether for sorting newly harvested crops, for real-time control of specific properties, or actually in the store or at the consumer’s home in order to check, for example, whether a foodstuff is edible or already spoiled. We’re seeking to develop a small, mobile food scanner (see overleaf) – along the lines of the tricorder from Star Wars – and thereby ensure that in the future less food ends up in the garbage can because the best-before date has expired.