It is estimated that around 100 billion items of clothing are currently produced worldwide, most of which will end up in recycling processes. Sorting these old textiles by hand requires an enormous amount of human labour. A research team is now developing new technologies that will enable robotic grippers to sort textiles more effectively.
The special research area “Mathematics of Reconstruction in Dynamical and Active Models”, funded by the Austrian Science Fund FWF, was launched in March 2025. Researchers from the University of Klagenfurt, led by Barbara Kaltenbacher (Department of Mathematics), will be contributing their expertise on inverse problems. The aim is to develop new mathematical tools for active, dynamic and model-based imaging modalities.
Using non-intrusive load monitoring (NILM), it is possible to analyse which devices in a household are currently consuming electricity without having to attach separate measuring instruments to all of the consumers. Emir Sinanović, a university assistant in the Smart Grids working group at the Department of Networked and Embedded Systems, hopes to combine this analysis with a large-language model that works rather like ChatGPT.
Traditionally, wind turbines have to be shut down before they can be inspected for damage. This means that these wind turbines do not generate energy during the shutdown period. Furthermore, inspection costs for wind turbines tend to be high. The DORBINE project, funded by the FFG, involves a research team from the University of Klagenfurt working with industrial partner AIR6 SYSTEMS to develop a new technology that uses artificial intelligence to control swarms of drones that inspect wind turbines while they are in operation.
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