1 citations · 1 across the 3 of their papers we have counts for
5 papers
SERVIMON: AI-Driven Predictive Maintenance and Real-Time Monitoring for Astronomical Observatories
Emilio Mastriani, Alessandro Costa, Federico Incardona +2
Objective: ServiMon is designed to offer a scalable and intelligent pipeline for data collection and auditing to monitor distributed astronomical systems such as the ASTRI Mini-Arr…
Segmentation over Complexity: Evaluating Ensemble and Hybrid Approaches for Anomaly Detection in Industrial Time Series
Emilio Mastriani, Alessandro Costa, Federico Incardona +2
In this study, we investigate the effectiveness of advanced feature engineering and hybrid model architectures for anomaly detection in a multivariate industrial time series, focus…
Improving Anomaly Detection in Industrial Time Series: The Role of Segmentation and Heterogeneous Ensemble
Emilio Mastriani, Alessandro Costa, Federico Incardona +2
Concerning machine learning, segmentation models can identify state changes within time series, facilitating the detection of transitions between normal and anomalous conditions. S…
Enhancing CTAO Monitoring and Alarm Subsystems in Distributed Environments Using ServiMon
Kevin Munari, Alessandro Costa, Federico Incardona +4
ServiMon is a scalable data collection and auditing pipeline designed for service-oriented, cost-efficient quality control in distributed environments, including the CTAO monitorin…
Predictive Maintenance Study for High-Pressure Industrial Compressors: Hybrid Clustering Models
Alessandro Costa, Emilio Mastriani, Federico Incardona +2
This study introduces a predictive maintenance strategy for high pressure industrial compressors using sensor data and features derived from unsupervised clustering integrated into…