Ipkovich, Ádám and Abonyi, János and Kummer, Alex (2026) ObServML: Deployable Python application for compact and modular systems monitoring. SoftwareX, 34. p. 102596. ISSN 23527110
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Official URL: https://doi.org/10.1016/j.softx.2026.102596
Abstract
ObservML enables the combination of training and deploying ML monitoring models within a single microservices-based system. Its application focuses on monitoring problems that can be solved with fault detection and isolation (FDI), time series analysis, and process mining through an operator-friendly and adaptable framework based on MLOps practices.
| Item Type: | Article |
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| Uncontrolled Keywords: | MLOps; Monitoring; Machine learning; Deep learning; Fault detection |
| Subjects: | Q Science / természettudomány > Q1 Science (General) / természettudomány általában T Technology / alkalmazott, műszaki tudományok > TP Chemical technology / vegyipar, vegyészeti technológia |
| Depositing User: | Dr. Alex Kummer |
| Date Deposited: | 18 Sep 2026 06:48 |
| Last Modified: | 18 Sep 2026 07:03 |
| URI: | https://real.mtak.hu/id/eprint/246687 |
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