Taking a closer look at electricity consumption with the help of artificial intelligence

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.

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AI-controlled drone swarms to inspect wind turbines in the future

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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Using innovative methods to improve our understanding of the interplay between monetary policy and the economy

How can we improve the prediction of systemic risks in financial and economic crises? A new research project is developing innovative Bayesian methods to model dynamic covariances – with the aim of improving forecasts and supporting political decisions.

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Online trainer corrects individually tailored movements

Since the pandemic, working out at home in front of the computer has become a habit for many. But are these exercises, be they for rehabilitation or athletic purposes, being performed correctly? Roman Dorrek is developing software that can identify whether individual movements are being performed in the most beneficial way possible.

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