Sensor Data Analysis

Industrie 4.0 environments typically comprise various (sensor) data sources, e.g., the communication infrastructure itself, sensors attached to autonomous entities like robots for intralogistics, and sensors attached to production tools.  This data can for example be used to optimize operation and planning, but also for quality control and optimization of maintenance processes. AIRPoRT tackles key questions for sustainable utilization of such sensor data:

• How can we handle the complexity of data generation on the shop floor?
  Here, AIRPoRT develops technology for contextualized data capturing.
• How can background knowledge be used to help interpreting sensor data?
  AIRPoRT extends current machine learning techniques for integrating semantic information and deep learning with the goal of more efficient, reliable and human-understandable data analysis.

This focus topic is co-ordinated by DFKI's Smart Data and Knowledge Services Department.