EventDetectR -- An Open-Source Event Detection System
Sowmya Chandrasekaran, Margarita Rebolledo, Thomas Bartz-Beielstein

TL;DR
EventDetectR is an open-source system that detects unexpected water quality events using multiple algorithms and residual analysis, demonstrating high reliability and performance in industrial water sensor data.
Contribution
The paper introduces a novel open-source event detection system that combines multiple modeling algorithms with residual analysis for water quality monitoring.
Findings
Reliable detection of water contamination events
Superior performance compared to existing methods
Effective use of multivariate sensor data
Abstract
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.
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Taxonomy
TopicsWater Quality Monitoring Technologies · Water Systems and Optimization · Hydrological Forecasting Using AI
