SS02 - Big Data And Machine Learning For Automation

Special Session Organizers

• Alexander Maier, OWL University of Applied Sciences
  [email protected]
• Dr.-Ing. Stefan Windmann, Fraunhofer-Anwendungszentrum Industrial Automation
  [email protected]
• Christian Frey, Fraunhofer IOSB
  [email protected]
• Prof. Dr. Oliver Niggemann, Institute Industrial IT, Lemgo, Germany
  [email protected]

Download SS02 Call For Papers (updated 2014-01-16)

Contents

In the future, the Internet of Things (IoT) will deliver a growing amount of data from production plants, rendering a manual analysis of these data impossible Therefore, any implementation of the Internet of Things will require corresponding methods for data analysis and machine learning. I.e. what is needed are Big Data solutions for the field of automation. But the IoT demands, for several reasons, other solutions than classical big data scenarios: E.g. measurements are time-dependent and unsynchronized. Furtheremore, all algorithms must be suited for embedded platforms.

We invite submissions of papers addressing aspects of data analysis, machine learning and Big Data in the field of automation and production. This special session will focus on (but not be limited to) the following topics in the area of:

• Data acquisition strategies in distributed plants
• Methods for storing data in the field of industrial automation
• Machine learning for condition monitoring and diagnosis
• Industrial applications of Big Data and machine learning
• Learning of behavior models for complex industrial processes
• Unsupervised and supervised learning from large amounts of data
• Visualzation of plant behaviour
• Self-optimization of complex industrial processes

Submission of Papers

Papers are to be submitted electronically. For further details, please consult the conference web pages.

Author's Schedule