SERIE2GRAPH

Automatically determine the health of a system, equipped with sensors, by detecting and graphically represent subsequence anomalies in a time series, without prior knowledge of the system.

Applications:

• Internet of Things
• Operation monitoring: aeronautics, automobiles, railways
• Industrial production site monitoring
• Control systems such as SCADA
• Health: monitoring physiological parameters
• Finance: fraud detection
• Computer data center operation health monitoring

Competitive advantages:

• No prior knowledge of the domain and anomaly characteristics
• No need of labeled instances (unsupervised method)
• Identification of anomalies of varying lengths
• Identification of single and recurrent anomalies of various types
• High accuracy and fast computing method

Keywords: Anomalies, Subsequence anomalies, Outliers, Time series, Data series