• COLABIS will design and implement a Web platform that enables and eases the development of urban early warning systems, specifically focusing on information fusion derived from sensors, crowdsourcing, geosimulations, as well as administrative and historical data. The project focusses on local heavy rain, flooding and cascading events affecting urban water and sewage infrastructures but also traffic infrastructures.

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  • © Fraunhofer IGD

    In this project, Fraunhofer IDM@NTU is collaborating with the Lee Kong Chian School of Medicine to develop a novel collaborative environment for group based learning in the classroom.

    Here, a multi-touch table for group discussions is linked to individual tablets of the students via a wireless client-server architecture. Digital content can be examined, passed between clients, and annotated using both the touch table as well as the tablets. Intuitive touch gestures are used as an easy way of interaction with the learning material provided by the teacher.

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  • © Fraunhofer IGD

    In dentistry, imaging data (X-rays) is the first source of information for an initial assessment of a patient’s dental health and is also the basis for further planning of a patient’s treatment. Both extraoral images, such as a panoramic radiograph or a lateral teleradiograph, and intraoral images, such as bitewing radiographs, are used. Panoramic radiographs are typically the first image since all of the teeth, including roots, are pictured very clearly.

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  • © Fraunhofer IKTS

    Since introduction to the market in the 1990’s, lithium-ion batteries have been applied in many fields such as every-day used, small electronics (smartphones, laptops), and much more specialized applications, for instance, electric vehicles or autonomous underwater vehicles (AOVs). Despite the many advantages of lithium-ion batteries, which give them an advantage on the market, they also have several limitations, which apply to each battery, regardless of chemistry or design.

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  • Eine visuelle Aufbereitung der Covid-19-Daten unterstützt Gesundheitsämter.
    © Fraunhofer IGD – Tine Casper

    Public health departments are facing a great challenge in obtaining available data on the spread of COVID-19, connecting it to other sources of data and analyzing it with regard to ever-pressing questions on how to proceed in combatting the virus. This is why CorASiV actively aids public health departments with visualization and analytics technology. The project addresses various leverage points in decision-making support for public health departments by using a flexible data set to expand both AI methods as well as smart analytical methods and models in combination with visualization.

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  • © Fraunhofer IGD

    Head/neck model with over 40 anatomical structures.

    Medical imaging data contains anatomical information that, given the volume of data and especially with radiological 3D imaging data, can no longer reasonably be marked/contoured by hand. The challenge for automatic processes is that not all anatomical regions stand out from their surroundings through strong differences in contrast. Nevertheless, radiologists are able to assign such regions in the imaging data. For automatic algorithms, this requires representing the anatomical knowledge of a clinical expert in a form that is comprehensible to the computer.

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  • Mass customization and 3D printing centres are a recent trend since a few years. But how to support novice designers and laymen in designing workable objects within some given design space for 3D printed objects? CUPstomizer is a prototype solution that integrates parametric modelling, simulation and optimization approaches to enable the user to vary design parameters and to guide him/her to choose parameters satisfying a goal function of maintaining stability while adding as little as possible material – all in an easy-to-use, interactive 3D application.

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  • © Fraunhofer IGD

    Data@Hand detects deviations from the normal operation of a ma-chine

    Data@Hand is an automated data analysis framework for various applications. Data@Hand can be used to quickly analyze data, detect anomalies early and draw conclusions about the significance of data. When used in predictive maintenance, issues can be analyzed to determine the cause, predicted and avoided in the future. Data@Hand connects AI tools to existing visual data processing platforms, such as Plant@Hand3D or Health@Hand.

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  • © DataBio Consortium

    The Data-Driven Bioeconomy project (DataBio) focuses on the production of best possible raw materials from agriculture, forestry and fishery for the bioeconomy industry to produce food, energy and biomaterials taking into account responsibility and sustainability.

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