Includes the full proceedings of the 2018 ML4CPS – Machine Learning for Cyber Physical Systems Conference
Presents recent and new advances in automated machine learning methods
Provides an accessible and succinct overview on machine learning for cyber physical systems, industry 4.0 and IOT
Part of the book series: Technologien für die intelligente Automation (TIA, volume 9)
Table of contents (15 papers)
About this book
This Open Access proceedings 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 Karlsruhe, October 23-24, 2018.
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.
- Machine Learning
- Artificial Intelligence
- Cognitive Robotics
- Internet of Things
- Computational intelligence
- Cyber-Physical Systems
- Computer-based algorithms
- Smart grid
- Open Access
Editors and Affiliations
Institut für Optronik, Systemtechnik und Bildauswertung, Fraunhofer, Karlsruhe, Germany
MRD, Fraunhofer Institute for Optronics, System Technologies and Image Exploitation IOSB, Karlsruhe, Germany
inIT - Institut für industrielle Informationstechnik, Hochschule Ostwestfalen-Lippe, Lemgo, Germany
About 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. Christian Kühnert is a senior researcher at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. His research interests are in the field of machine-learning, data-fusion and data-driven condition monitoring.
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.
Book Title: Machine Learning for Cyber Physical Systems
Book Subtitle: Selected papers from the International Conference ML4CPS 2018
Editors: Jürgen Beyerer, Christian Kühnert, Oliver Niggemann
Series Title: Technologien für die intelligente Automation
Publisher: Springer Vieweg Berlin, Heidelberg
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2019
License: CC BY
Softcover ISBN: 978-3-662-58484-2
eBook ISBN: 978-3-662-58485-9
Series ISSN: 2522-8579
Series E-ISSN: 2522-8587
Edition Number: 1
Number of Pages: VII, 136