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Scalable Fleet Monitoring and Visualization for Smart Machine Maintenance and Industrial IoT Applications.

, , , , , , , , and . Sensors, 20 (15): 4308 (2020)

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A generalized matrix profile framework with support for contextual series analysis., , , , , , and . Eng. Appl. Artif. Intell., (2020)Automated Extraction of Rules and Knowledge from Risk Analyses: a Ventilation Unit Demo., , , , , , , , and . ISWC (P&D/Industry/BlueSky), volume 2180 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)A Dynamic Dashboarding Application for Fleet Monitoring Using Semantic Web of Things Technologies., , , , , , , and . Sensors, 20 (4): 1152 (2020)Benchmarking Whole Knowledge Graph Embedding Techniques., , , , and . Int. J. Softw. Eng. Knowl. Eng., 34 (1): 163-184 (January 2024)Scalable Fleet Monitoring and Visualization for Smart Machine Maintenance and Industrial IoT Applications., , , , , , , , and . Sensors, 20 (15): 4308 (2020)FLAGS: A methodology for adaptive anomaly detection and root cause analysis on sensor data streams by fusing expert knowledge with machine learning., , , , , , , , , and 1 other author(s). Future Gener. Comput. Syst., (2021)Hierarchical pattern matching for anomaly detection in time series., , , , , , , , and . Comput. Commun., (2022)Towards Adaptive Anomaly Detection and Root Cause Analysis by Automated Extraction of Knowledge from Risk Analyses., , , , , , , , and . SSN@ISWC, volume 2213 of CEUR Workshop Proceedings, page 17-31. CEUR-WS.org, (2018)Unsupervised Anomaly Detection for Communication Networks: An Autoencoder Approach., , , , , , and . IoT Streams/ITEM@PKDD/ECML, volume 1325 of Communications in Computer and Information Science, page 160-172. Springer, (2020)