Automated capturing, analysis and storing of relevant building data is increasing in significance. Despite the advances in information and communication technologies made so far, measuring quality can be influenced considerably by sensor errors. In this joint research project Professor Dr.-Ing. Kay Smarsly, Professor of Computing in Civil Engineering, and Dipl.-Ing. Oliver Hahn, MKP GmbH, are aiming to continue improving the reliability of digital building monitoring. 

On the basis of an artificial intelligence approach, errors and faulty calibrations in sensor technology are to be recognised and resolved independently by the monitoring system in future. The researchers emphasise that complex computer models are not required in this connection. Errors are instead localised by means of patterns occurring in the measurement data. This approach has already been theoretically tested and is now to be practically implemented using the example of a railway bridge near Weimar. 

The »mFUND« of BMVI:
Within the scope of the »mFUND« research initiative, beginning in 2016, BMVI has been supporting research and development projects which focus on data-based digital applications for mobility 4.0. In addition to financial support, the mFUND supports networking between stakeholders from the fields of politics, the economy and research by means of various types of events, and also provides access to the »mCLOUD« data portal. Further information can be found at www.mfund.de.

Project: Feasibility study on data-based error diagnostics in monitoring systems for infrastructure - Dafmon

Duration: 05/2019 -04/2020

Funded by: Federal Ministry of Transport and Digital Infrastructure (BMVI), mFUND

Project partner:

The Bauhaus-Universität Weimar
Faculty of Civil Engineering
Prof. Dr.-Ing. Kay Smarsly, Computing in Civil Engineering

MKP GmbH
Dipl.-Ing. Oliver Hahn

Contact partner:
Please contact Professor Dr.-Ing. Kay Smarsly, The Bauhaus-Universität Weimar, Faculty of Civil Engineering, Computing in Civil Engineering, by Tel.: +49 3643 58 4214 or via email: kay.smarsly[at]uni-weimar.de if you have any questions about the project.