Cited 3 time in webofscience Cited 3 time in scopus

Impact of sensor measurement error on sensor positioning in water quality monitoring networks

Impact of sensor measurement error on sensor positioning in water quality monitoring networks
Kim, Seong HeeAral, Mustafa M.Eun, Yong SoonPark, Jisu J.Park, Chul Jin
DGIST Authors
Eun, Yong Soon
Issue Date
Stochastic Environmental Research and Risk Assessment, 31(3), 743-756
Article Type
Article in Press
AlgorithmsErrorsImage ResolutionLocationMeasurement Error ModelsMeasurement ErrorsOptimal Sensor LocationsOptimizationOptimization AlgorithmsProbabilistic ModelingProcess ControlQuality ControlSensor Measurement ErrorsSensor MeasurementsSensor NetworksSimulation OptimizationStatistical Process Controls (SPC)Water QualityWater Quality Monitoring
This paper studies the impact of sensor measurement error on designing a water quality monitoring network for a river system, and shows that robust sensor locations can be obtained when an optimization algorithm is combined with a statistical process control (SPC) method. Specifically, we develop a possible probabilistic model of sensor measurement error and the measurement error model is embedded into a simulation model of a river system. An optimization algorithm is used to find the optimal sensor locations that minimize the expected time until a spill detection in the presence of a constraint on the probability of detecting a spill. The experimental results show that the optimal sensor locations are highly sensitive to the variability of measurement error and false alarm rates are often unacceptably high. An SPC method is useful in finding thresholds that guarantee a false alarm rate no more than a pre-specified target level, and an optimization algorithm combined with the thresholds finds a robust sensor network. © 2016, Springer-Verlag Berlin Heidelberg.
Springer New York LLC
Related Researcher
  • Author Eun, Yongsoon DSC Lab(Dynamic Systems and Control Laboratory)
  • Research Interests Resilient control systems; Control systems with nonlinear sensors and actuators; Quasi-linear control systems; Intelligent transportation systems; Networked control systems
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Department of Information and Communication EngineeringDSC Lab(Dynamic Systems and Control Laboratory)1. Journal Articles

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