Real-time High Performance Anomaly Detection over Data Streams
Dimitrije Jankov, Sourav Sikdar, Rohan Mukherjee, Kia Teymourian, Chris Jermaine · 2017
Real-time analytics over data streams are crucial for a wide range of use cases in industry and research. Today's sensor systems can produce high throughput data streams that have to be analyzed in real-time. One important analytic task is anomaly or outlier detection from the streaming data. In many industry applications, sensing devices produce a data stream that can be monitored to know the correct operation of industry devices and consequently avoid damages by triggering reactions in real-time.