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  • © AIOLOS 2022

    The AIOLOS project (Artificial Intelligence Tools for Outbreak Detection and Response) has received approval from the French and German governments to develop a digital platform designed to allow for early detection of new respiratory pathogens epidemics, monitor their spread and inform decisions on appropriate counter measures. AIOLOS will provide insights for private and public decision-making in a web-based dashboard, which leverages real-time data from multiple data sources, advanced artificial intelligence (AI), and predictive modeling. Sanofi in France and the Fraunhofer Institutes SCAI and ITMP in Germany lead the consortium, which includes four other French and German partners: CompuGroup Medical, Quinten Health, Impact Healthcare and umlaut, part of Accenture. The project is supported by the French State and the German Federal Ministry for Economic Affairs and Climate Action in the context of the Franco-German call on Artificial Intelligence technologies for risk prevention, crisis management and resilience. This call for projects operated by Bpifrance, on behalf of the French government as part of the France 2030 investment plan, and by DLR Projektträger, aims to support innovation projects between France and Germany on artificial intelligence technologies.

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  • Anuga FoodTec: Process Simulation with MESHFREE / 2022

    Innovative Simulation for the Food Industry

    Press Release / April 20, 2022

    Eine sprühende Vollkegeldüse: links im Experiment, rechts in der Simulation.
    © Fraunhofer IVV/Fraunhofer ITWM

    Whether cleaning, stirring, kneading ,or injection processes – MESHFREE can be used to reliably simulate food technology processes. The software product developed by the Fraunhofer Institutes for Industrial Mathematics ITWM and for Algorithms and Scientific Computing SCAI uses grid-free simulations to map physical processes. This year, the institutes will again be represented at Anuga FoodTec from April 26 to 29 in Hall 7.1 at Stand A049.

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  • The Fraunhofer Institute for Algorithms and Scientific Computing SCAI and the software company Kairntech (Grenoble) have created a knowledge graph for psychiatric disorders, especially psychoses. Knowledge graphs allow unstructured texts to be represented in a structured, comparable format. They visualize cause-and-effect models to help medical professionals make decisions about therapies.

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  • © ITEA

    VMAP, an international collaborative ITEA project led by Fraunhofer SCAI, has created a vendor-neutral standard for CAE data storage and transfer to enhance interoperability in virtual engineering workflows, which has already been adopted by a lot of tool providers. The VMAP Standard Community will be established to further disseminate the VMAP Standard and its development. Thanks to these outstanding outcomes, VMAP received the ITEA Award of Excellence for Standardisation today.

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  • © Fraunhofer SCAI

    The treatment of people who have Parkinson's disease can be improved significantly by using digital techniques. The DIGIPD project explores how artificial intelligence can contribute to a better individualized treatment of the disease, for example, by analysis of sensor data or automatically detected changes in speech, facial expressions, or movements.

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  • Fraunhofer SCAI has greatly improved its successfully marketed AutoPanelSizer software. The new version now optimizes plans for cutting rectangular parts much faster. New features and the utilization of multiple processor cores ensure even more efficient cutting plans. As a pure optimization kernel, the software can be integrated into existing plant control systems or ERP/MES systems.

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  • © Fraunhofer SCAI

    With the new website "covid19-knowledgespace.de", Fraunhofer SCAI – together with Fraunhofer IME, Fraunhofer IAIS, the Information Center for Life Sciences ZBMED and other research partners – is opening a new kind of knowledge space with analysis tools and information on COVID-19. Central services in the COVID-19 Knowledge Space are the Biomedical Knowledge Miner "BiK>Mi" containing a highly curated cause-and-effect model for SARS-CoV-2, the literature mining environment "SCAIView", which has been optimized for COVID-19 text mining, and a special terminology representing major entities and concepts of COVID-19.

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  • © Fraunhofer SCAI

    Electricity from renewable energy sources contributes to combat climate change. One of the challenges is to develop technologies for storing excesses in energy supplies quickly and without loss. Organic redox flow batteries (RFBs) promise a viable route to this end: operated where needed, they rely on matter-bound storage – just in analogy to nature's example.

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  • An answer to the challenges of transitioning to renewables / 2020

    Fraunhofer connects energy production and storage

    Research News / January 02, 2020

    © Fraunhofer SCAI

    The good news is that renewables account for nearly 50 percent of electricity generated in Germany. The bad news is that they lack the flexibility to adapt to the day’s fluctuating electricity demand. They only furnish electrical energy when the wind blows or the sun shines. In a perfect world, engineers would find a way to store the vast amounts of energy generated by renewables and coordinate power production and storage. And that is exactly what ES-FLEX-INFRA, a joint project led by the Fraunhofer Institute for Algorithms and Scientific Computing SCAI, aims to do.

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