Industrie 4.0

Data analytics for the fourth industrial revolution, such as proactive service and maintenance of production resources or finding anomalies in production processes.



Data-driven aspects of medicine are explored, such as the need-driven care of patients or IT controlled medical technology.


Smart Infrastructure

Untersuchung datengetriebener Aspekter städtischen Lebens, bspw. der Verkehrssteuerung, der Müllentsorgung oder der Katastrophenbewältigung, bedarfsgesteuerte Optimierung von Verbrauchsmodellen, basierend auf Daten intelligenter Stromzähler.

Featured Projects

  • SDSC-BW: Smart data analysis to predict the state of industrial process water

    Water plays an important role in many industrial processes. A smooth running of complex process water systems is the requirement for a functioning cooling process. Different sizes and measured values are decisive. These include, among others, the pH value, the redox value or the conductivity of the system water. In order to monitor these values, a wide variety of sensors capture and make data available.

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    MedTrend1: Smart Data Prediction of Trends in Medicine

    MedTrend1 is a proof-of-concept study that aims at identifying social trends with medical relevance out of large amounts of Smart Data. For a successful study, it is crucial to combine Smart Data acquisition, on the one hand, with smart analysis on the other hand.

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    SDSC-BW: Potential Analysis for Leather-Cutting Optimization

    The cutting optimization of natural leather is a highly sophisticated process that already factors in the different quality characteristics of the leather hides while placing the cutting templates. Not only the underlying natural product leather but also the furniture manufactured from it – individually and just-in-time – are available in many variants. For this reason, a flexible and individual consultation regarding Smart Data was especially important for Rolf Benz as an individual manufacturer.

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  • GPU + In-Memory Data Management for Big Data Analytics

    The global rollout of Smart Meters opens a new business paradigm for utilities with data collection/transaction at such a high volume and velocity. In this project, we develop a toolchain based on In-Memory Data Management and Parallel Data Processing in the GPU. Our aim is to use the processing power of the GPU and the high-throughput and low-latency features of In-Memory databases to develop an adequate Big Data analytics platform. Although the project is primarily concerned with the use case of Smart Meter data, the tool chain is also applicable for Big Data analytics in other domains.

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    Condition-Based Maintenance

    The enterprise “TRUMPF Machine Tools” is the global leader in the production of machine tools for sheet metal forming (laser, punching, and bending machines). At specified, but irregular intervals a “digital image” in the form of a data collection of logging and configuration information is created in a TRUMPF machine tool. Using these data, the project being planned aims at detecting deviations (anomalies) from the so-called “normal operation” and revealing correlations to yet unknown factors.

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