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Machine Learning for Cyber Physical Systems

Selected papers from the International Conference ML4CPS 2017

  • Jürgen Beyerer
  • Alexander Maier
  • Oliver Niggemann
Conference proceedings

Part of the Technologien für die intelligente Automation book series (TIA, volume 11)

Table of contents

  1. Front Matter
    Pages I-VII
  2. Martin Lachmann, Tilman Stark, Martin Golz, Eberhard Manske
    Pages 9-16
  3. Katharina Giese, Jens Eickmeyer, Oliver Niggemann
    Pages 17-23
  4. Felix Reinhart, Sebastian von Enzberg, Arno Kühn, Roman Dumitrescu
    Pages 25-33
  5. Ljiljana Stojanovic
    Pages 35-42
  6. Andreas Bunte, Peng Li, Oliver Niggemann
    Pages 43-51
  7. Marta Fullen, Peter Schüller, Oliver Niggemann
    Pages 53-61
  8. Heinrich Warkentin, Meike Wocken, Alexander Maier
    Pages 63-71
  9. Thomas Lewien, Ivan Slimak, Pyare Püschel
    Pages 81-87

About these proceedings

Introduction

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It  contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 25th-26th, 2017. 

Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

The Editors

Prof. Dr.-Ing. Jürgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB.

Dr. Alexander Maier is head of group Machine Learning at Fraunhofer IOSB-INA. His focus is on the development of algorithms for big data applications in Cyber-Physical Systems (diagnostics, optimization, predictive maintenance) and the transfer of research results to industry.      

Prof. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.

Keywords

Machine Learning Artificial Intelligence Cognitive Robotics Internet of Things Computational intelligence Cyber-Physical Systems Computer-based algorithms Smart grid Big Data Data Mining

Editors and affiliations

  • Jürgen Beyerer
    • 1
  • Alexander Maier
    • 2
  • Oliver Niggemann
    • 3
  1. 1.Institut für Optronik, Systemtechnik und BildauswertungFraunhoferKarlsruheGermany
  2. 2.Industrial AutomationFraunhofer-AnwendungszentrumLemgoGermany
  3. 3.inIT - Institut für industrielle InformationstechnikHochschule Ostwestfalen-LippeLemgoGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-59084-3
  • Copyright Information Springer-Verlag GmbH Germany, part of Springer Nature 2020
  • Publisher Name Springer Vieweg, Berlin, Heidelberg
  • eBook Packages Intelligent Technologies and Robotics
  • Print ISBN 978-3-662-59083-6
  • Online ISBN 978-3-662-59084-3
  • Series Print ISSN 2522-8579
  • Series Online ISSN 2522-8587
  • Buy this book on publisher's site
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