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Distributed Sensor Fusion in Water Quality Event Detection

Journal of Water Resources Planning and Management

Koch, Mark W.; Mckenna, Sean A.

To protect drinking water systems, a contamination warning system can use in-line sensors to indicate possible accidental and deliberate contamination. Currently, reporting of an incident occurs when data from a single station detects an anomaly. This paper proposes an approach for combining data from multiple stations to reduce false background alarms. By considering the location and time of individual detections as points resulting from a random space-time point process, Kulldorff's scan test can find statistically significant clusters of detections. Using EPANET to simulate contaminant plumes of varying sizes moving through a water network with varying amounts of sensing nodes, it is shown that the scan test can detect significant clusters of events. Also, these significant clusters can reduce the false alarms resulting from background noise and the clusters can help indicate the time and source location of the contaminant. Fusion of monitoring station results within a moderately sized network show false alarm errors are reduced by three orders of magnitude using the scan test. © 2011 ASCE.

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TYPE Journal Article YEAR 2010
OSTIScopus

Integrating event detection system operation characteristics into sensor placement optimization

Hart, David B.; Hart, William E.; Mckenna, Sean A.; Phillips, Cynthia A.

We consider the problem of placing sensors in a municipal water network when we can choose both the location of sensors and the sensitivity and specificity of the contamination warning system. Sensor stations in a municipal water distribution network continuously send sensor output information to a centralized computing facility, and event detection systems at the control center determine when to signal an anomaly worthy of response. Although most sensor placement research has assumed perfect anomaly detection, signal analysis software has parameters that control the tradeoff between false alarms and false negatives. We describe a nonlinear sensor placement formulation, which we heuristically optimize with a linear approximation that can be solved as a mixed-integer linear program. We report the results of initial experiments on a real network and discuss tradeoffs between early detection of contamination incidents, and control of false alarms.

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TYPE Conference YEAR 2010
OSTI
Results 51–75 of 194
Results 51–75 of 194