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Research project (§ 26 & § 27)
Duration : 2024-05-01 - 2027-04-30

CircularFoods has set itself the goal of making the best possible use of regionally available food residues and producing new high-quality products from such residues. In a circular approach, CircularFoods aims to obtain high-quality protein components from various residual materials, investigate the effects on possible subsequent biogas production, and develop innovative liquid biofertilizers, new growing media (peat substitutes) and fertilizer pellets from the fermentation residues (possibly in a mixture with other residual material fractions). The best possible cascading use should contribute to a significant increase in the added value of food residues and, in line with the Austrian circular economy strategy, to maximum material use in combination with possible biogas production (not the focus of research in this project). The use of energy-efficient processes and research into optimal carbon utilization via the cascading approach should lay the foundation for the long-term vision of a climate-positive food cycle.
Research project (§ 26 & § 27)
Duration : 2023-08-01 - 2026-07-31

Raising awareness and modelling the forest fire danger are essential aspects of preventive measures for an integrated forest fire management. In Austria, there are currently only a few initiatives for rising awareness about the current fire danger and platforms that support the modelling. The Institute of Silviculture is currently running the prototype of an integrated system for forest fire risk assessment (waldbrand.at) and the only forest fire blog (fireblog.boku.ac.at). These two established platforms require constant support and further development. Within the scope of this project, measures are therefore to be taken to ensure the functionality and performance, conduct necessary updates and bug fixes as well as ensure the security of both platforms. Additionally new functionalities should be implemented and a higher media outreach should be achieved through cooperations with different target groups and communication channels. The platforms should be used as an expert tool for forest fire danger assessment, bundle existing knowledge on forest fires and serve as an effective communication channel in close cooperation with ongoing forest fire projects.
Research project (§ 26 & § 27)
Duration : 2024-03-01 - 2028-05-01

In this project, novel scenarios are tested and evaluated, and work is done on how to bring "common sense" into robots. The approach followed is "human-in-the-loop", combining the advantages of human experts with the advantages of AI. Specifically, this project tests and evaluates deployment scenarios of robots in forestry technology and presents new deployment scenarios. The novelty of this approach allows us to explore basics in terms of requirements, challenges and future possibilities in dealing with such systems, thus paving the way for more advanced basic projects or applications. Specifically, this project is expected to result in a series of international publications and an infrastructure to research and test the fundamentals for the use of future AI technologies and to apply them in teaching. Finally, the emerging robot test park in Tulln – adjacent to the new House of Digitalization - may also generate broad interest in the topic. The research methodology follows a 3G pioneer research approach with agile human-centered design: generation 1 testing of existing technology, generation 2 adaptation of existing technology with low-cost means, generation 3 advanced adaptation that goes beyond the state of the art and is planned together with our partners in Canada and UK - world leading robotics institutes. The infrastructure funded by this proposal will serve existing projects and is intended to spur new, larger projects (e.g.,EU). Added values are planned on three levels: 1) for the international AI research community through publications, 2) for the state of Lower Austria through a) later practical usage possibilities, and b) as an important contribution to teaching and making AI education more attractive to young researchers to counteract the labor shortage in AI.

Supervised Theses and Dissertations