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

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    Requirement analysis for energetic construction measures based on historical infrastructure data

    Over several years, the KIT-FM (Facility Management) has collected data with immense value for the operational management, but also for the planning and implementation of future infrastructure developments. This data is also of great interest for researchers. On the one hand, we will examine how the existing infrastructure data evaluated by Smart Data methods can help to draw more accurate conclusions about the operational management and the infrastructure planning. On the other hand, we will drive forward the usability of this data for research and innovation projects.

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    All-Time Parts Prediction (ATP) Demo

    ATP predicts the demand for service parts (especially in the automotive industry) for so-called long-time-buy or all-time-buy decisions. This future demand may cover the next 10-20 years and is difficult to estimate, which often leads to buying way too much. Consequently, after many years of sitting in the warehouse, at the end, huge amounts need to be scrapped. This causes high inventory and warehousing costs, which can be significantly reduced by more accurate demand predictions. The IBM ATP Solution has been developed to do exactly that: to predict all-time demand with high accuracy.

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  • SDSC-BW: Smart Data supported campaign analysis for marketing

    With the speed in which IT topics are now being pushed forward, even media companies have to adapt more quickly and become flexible. In particular, this includes marketing and sales activities in order to keep the customers satisfied and to raise further potential. For the analysis project of the Smart Data Solution Center Baden-Württemberg (SDSC-BW), the Huber publishing company provided anonymised information about the concluded contracts of their services. The contracts and customer data, as well as the related marketing activities, were collected over a period of 72 months. In total, information from 943 database tables was processed and a quarter of a million data sets were analyzed and evaluated.

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  • 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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