The Software Campus project SENSE addresses data collection and data analysis in the Internet of Things.
By connecting more and more devices and sensors, the amount of available data is increasing rapidly. The consulting company Gartner estimates a quadrupling of devices connected via the Internet during the next years [http://www.gartner.com/newsroom/id/3165317]. Such an amount of devices with sensors will produce a huge amount of data streams (massiv-sesor-data). The aggregation, optimazation of the analyses of these mostly unstructured datastreams, and the prediction of important events as soon as possible, is very important especially for industrial facilities. While the theoretical value of analyzing this data is undisputed, the practical implementation presents a great challenge.
We have two well-known approaches for those kind of problems:
The SENSE project explores ways to dynamically tune the data collection to current analyses. As a result, analysis systems gain control over the production of data streams. This allows for providing tailored data streams based on the data demand of applications, which enables applications to connect to a vast amount of sensor at small data transfer costs.
As a result, data analysis application can derive in-sights from millions of data sources, which enables diverse Internet of Things application which were economically or technically impossible before. The contributions of the project are generally applicable to a wide range of systems and applications. Thus, the project serves as foundation for a resource efficient Internet of Things.
Project Duration: 05/2016 - 04/2018