Applied IoT Data Analytics

Basic data for this project

Type of project: Own resources project

Duration at the University of Münster: since 01/04/2017

Description

Keywords: Applied IoT Data Analytics

Project management at the University of Münster

Beecks, Christian

Professorship of practical computer science (Prof. Beecks)

Publications of the University of Münster resulting from the project

Unsupervised Anomaly Detection in Production Lines Grass A, Beecks C, Soto JAC (2018) In: (eds.), Selected papers from the International Conference on Machine Learning for Cyber Physical Systems, ML4CPS 2018, Karlsruhe, Germany, October 23-24, 2018, 18-25. Springer. doi:10.1007/978-3-662-58485-9\_3 Research article in edited proceedings (conference) \| Peer reviewed \| Published
Machine Learning for Enhanced Waste Quantity Reduction: Insights from the MONSOON Industry 4.0 Project Beecks C, Devasya S, Schlutter R (2018) In: (eds.), Selected papers from the International Conference on Machine Learning for Cyber Physical Systems, ML4CPS 2018, Karlsruhe, Germany, October 23-24, 2018, 1-6. Springer. doi:10.1007/978-3-662-58485-9\_1 Research article in edited proceedings (conference) \| Peer reviewed \| Published
Gaussian Processes for Anomaly Description in Production Environments Beecks C, Schmidt KW, Berns F, Grass A (2019) In: (eds.), Proceedings of the Workshops of the Joint Conference on Extending Database Technology and Database Theory, EDBT/ICDT 2019, Lisbon, Portugal, March 26, 2019. CEUR-WS. Research article in edited proceedings (conference) \| Peer reviewed \| Published
Metric Indexing for Efficient Data Access in the Internet of Things Beecks C, Grass A, Devasya S (2018) In: (eds.), IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 5132-5136. (kein Verlag angegeben). doi:10.1109/BigData.2018.8622387 Research article in edited proceedings (conference) \| Peer reviewed \| Published