dr. ir. Pieter Moens
- ORCID iD
- 0000-0003-2035-8766
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- PhD Thesis
- open access
Context-Aware Machine Learning for Scalable IoT Data Analytics and Visualization Using Semantic Web Technologies
(2024) -
- Conference Paper
- P1
- open access
Edge anomaly detection framework for AIOps in Cloud and IoT
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- Journal Article
- A1
- open access
A microservice architecture for leak localization in water distribution networks using hybrid AI
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- Conference Paper
- C1
- open access
From self-reporting to monitoring for improved migraine management
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- Conference Paper
- C3
- open access
Context-aware visualization recommendations reduce decision overload for operators
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- Journal Article
- A1
- open access
A semi-supervised approach with monotonic constraints for improved remaining useful life estimation
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- Journal Article
- A1
- open access
A complete software stack for IoT time-series analysis that combines semantics and machine learning-lessons learned from the dyversify project
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- Journal Article
- A1
- open access
Event-driven dashboarding and feedback for improved event detection in predictive maintenance applications
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- Journal Article
- A1
- open access
FLAGS : a methodology for adaptive anomaly detection and root cause analysis on sensor data streams by fusing expert knowledge with machine learning
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- Journal Article
- A1
- open access
Scalable fleet monitoring and visualization for smart machine maintenance and industrial IoT applications