EventDetectR -- An Open-Source Event Detection System
This work addresses water contamination event detection for industrial monitoring, but it appears incremental as it builds on existing event detection methods without introducing a major breakthrough.
The authors tackled the problem of detecting unexpected water quality conditions by developing EventDetectR, a system that uses multiple algorithms to model multivariate signals and residuals for event probability, and tested it on industrial sensor data, showing reliable performance with better results.
EventDetectR: An efficient Event Detection System (EDS) capable of detecting unexpected water quality conditions. This approach uses multiple algorithms to model the relationship between various multivariate water quality signals. Then the residuals of the models were utilized in constructing the event detection algorithm, which provides a continuous measure of the probability of an event at every time step. The proposed framework was tested for water contamination events with industrial data from automated water quality sensors. The results showed that the framework is reliable with better performance and is highly suitable for event detection.