Artificial Sensor Data Generation for CPS

Our Professorship is actively involved in exploring algorithms within the domain of Cyber-Physical Systems (CPS), emphasizing the essential role of comprehensive, real-world datasets for impactful research and development in this field. Due to the scarcity of such datasets in CPS, our focus is on the artificial generation of sensor data to fulfill the extensive data needs essential for developing and evaluating AI models.

Our developed model, grounded in system theory, is adept at emulating data structures found in real-world CPS and generating varied datasets, enabling nuanced comparisons of machine learning methods, particularly in unsupervised learning.

Access the artificial dataset here:

Access Dataset

For additional insights and methodologies, please refer to our publication: Access Publication. The source code is currently under review and will be available shortly. For more information, please contact Bernd Zimmering.


Letzte Änderung: 28. September 2023