Eisenstadt, 27 March 2025 Farmers use numerous resources such as seeds, fertilisers and water to cultivate high-yielding fields. However, not all areas deliver satisfactory yields despite the high use of resources. This is where AISAAC comes in: By using artificial intelligence and high-resolution satellite data, a system is being developed that enables small-scale yield forecasts. This allows areas to be identified that are more suitable for renaturalisation measures, while valuable agricultural land remains used efficiently.
Agriculture and innovative solutions
‘A particular focus is on optimising irrigation systems,’ explains project manager Marcus Hofmann. Research Burgenland has already looked at agricultural applications in the DIH Süd project: ‘In particular, the digitalisation of agriculture and irrigation systems for agricultural land, which have so far been based on a small database. As part of AISAAC, an AI-supported methodology is now being developed to optimise irrigation through the use of soil sensors and modern analysis techniques’.
Test points are specifically defined on agricultural land where sensors record data on soil moisture. ‘The AI analyses this data and provides precise recommendations on which sub-areas should be irrigated when and how intensively. This not only increases measurement accuracy, but also improves data transfer and makes it easier for farmers to use efficient irrigation techniques,’ explains project team member Clemens Gnauer.
Research Burgenland as a pacemaker for digital innovationsForschung Burgenland is contributing its extensive expertise in IoT sensor technology, GIS analyses and AI applications to the project. ‘Through close cooperation with other scientific partners, state-of-the-art technologies are being tested and further developed. We see this project as the starting signal to build up the research area of agricultural and nutritional science,’ says Marcus Keding, Managing Director of Forschung Burgenland. Innovative agricultural research projects such as AISAAC are a key driver for the competitiveness and sustainability of agriculture. ‘Through the targeted use of AI and modern sensor technologies, we enable resource-conserving farming, reduce operating costs and increase yields. At the same time, our research creates practical solutions that help farmers to work more efficiently and position themselves for the future. In this way, we combine economic benefits with ecological responsibility.’
