Name of the participant: Martin Kiefer
Description of the IT-research project:
The analysis of massive data streams is one of the great technical challenges of the future. The Internet of Things (IoT) is an important trend with great economic significance. The consulting firm Gartner estimates that the number of devices connected to the Internet will more than double in the next three years from 8.3 billion (2017) to 20.4 billion (2020).
Another important trend is the optimization of industrial manufacturing processes through modern information and communication technology (Industry 4.0). The result of both trends is an immense number of data sources, such as mobile devices or sensors, which provide data continuously and at high frequency. The evaluation of these data streams, which are massive in terms of number and data rates, offers great potential for new services and decision making, but the evaluation of massive data streams is a challenge from an algorithmic and technical point of view, since the potentially unlimited amount of data can only be cached and processed to a limited extent.
Carrying out analyses in these scenarios as efficiently and cost-effectively as possible is also of great importance for Germany as a location for industry and research. In this project, possibilities are explored to achieve this goal by means of approximations and modern hardware.
Software Campus partners: TU Berlin, Huawei
Implementation period01.04.2018 – 31.03.2020