Optimal placement of imperfect water quality sensors in water distribution networks

Winter, Casper de C.D.; Palleti, Venkata Reddy; Worm, D.; Kooij, Robert E.

doi:10.1016/j.compchemeng.2018.10.021

Cited by 45 publications

(25 citation statements)

References 30 publications

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“…There are some limitations with the water quality sensor as some contaminants may not be detected due to the low sensitivity of the sensor at low concentration and the existence of new types of emerging contaminants [27]. Furthermore, the long transmission delays and slow response time of data capturing will cause the result to be inaccurate, the result may vary when there is changes in the contaminants' concentration and the sensor could not take an immediate response on this matter [7].…”

Section: Water Quality Sensor and Microfluidic Sensormentioning

confidence: 99%

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Review on water quality monitoring technologies

Ting

Yee

2020

IJEECS

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<span>Water quality monitoring is always the prior element to ensure the drinking water is safe to be consumed. A lot of researches have been carried out over the past decades to design and develop a robust and cost-effective water monitoring system. The conventional water monitoring techniques were based on laboratory instruments which is time-consuming and laborious. Furthermore, it is not suitable when the water sampling point is far from the commercial laboratory centres. These limitations were then been solved by the developments of portable testing kits and microwave technique. The microwave techniques such as spectroscopy techniques and microwave sensor approach have improved the water quality monitoring experience which is convenient without sacrificing the measurement accuracy and sensitivity. Its portability enables the on-site measurement at rural areas and thus reduce the transportation and manpower cost. This paper intends to review the water contaminant detection techniques which include standardized drinking water parameter testing and microwave-based in terms of physical, chemical and microbiological parameters. Furthermore, this review also emphasizes the current trend of the water quality testing method in microwave technique. At the end of this paper, a significant advantages and drawbacks of the techniques are summarized, and recommendations are provided for future development in the water quality monitoring.</span>

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Section: Water Quality Sensor and Microfluidic Sensormentioning

confidence: 99%

“…Microwave sensor-based method involved the use of smart sensor to monitor water quality [6]. This model has been adopted in various water contaminants detection which include water quality sensor, microfluidic sensors and spectroscopy technique [7]. Water quality sensor has been introduced at the early of 1900s.…”

Section: Introductionmentioning

confidence: 99%

Review on water quality monitoring technologies

Ting

Yee

2020

IJEECS

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“…We adopt E and V to be the vertices of the water network graph. The monitoring sets were formed as follows: if a water flow from contamination source e passes through v, then e belongs to E v [23]. Criticality w e in this case can characterize the normalized population affected by contaminants injected in e [24].…”

Section: Numerical Studymentioning

confidence: 99%

A Network Monitoring Game with Heterogeneous Component Criticality Levels

Milošević

Dahan

Amin

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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We consider an attacker-operator game for monitoring a large-scale network that is comprised on components that differ in their criticality levels. In this zero-sum game, the operator seeks to position a limited number of sensors to monitor the network against an attacker who strategically targets a network component. The operator (resp. attacker) seeks to minimize (resp. maximize) the network loss. To study the properties of mixed-strategy Nash Equilibria of this game, we first study two simple instances: (i) When component sets monitored by individual sensor locations are mutually disjoint; (ii) When only a single sensor is positioned, but with possibly overlapping monitoring component sets. Our analysis reveals new insights on how criticality levels impact the players equilibrium strategies. Next, we extend a previously known approach to obtain an approximate Nash equilibrium for the general case of the game. This approach uses solutions to minimum set cover and maximum set packing problems to construct an approximate Nash equilibrium. Finally, we implement a column generation procedure to improve this solution and numerically evaluate the performance of our approach.

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“…In the process, the search is limited to the set of sensor layouts that make a predened set of variables of interest observable. The relative improvement of precision is one way among many to evaluate practical observability (e.g., Waldra et al, 1998;Chmielewski et al, 2002;Chang et al, 2012;Serpas et al, 2013;Mukherjee et al, 2017;Rico-Ramirez et al, 2007;Joshi and Boyd, 2008;Soldevila et al, 2018;de Winter et al, 2019;Nahar et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems – With application to wastewater treatment plants

Villez

Vanrolleghem

Corominas

2020

Computers & Chemical Engineering

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The advent of aordable computing, low-cost sensor hardware, and highspeed and reliable communications have spurred ubiquitous installation of sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance eorts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance

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Optimal placement of imperfect water quality sensors in water distribution networks

Cited by 45 publications

References 30 publications

Review on water quality monitoring technologies

Review on water quality monitoring technologies

A Network Monitoring Game with Heterogeneous Component Criticality Levels

A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems – With application to wastewater treatment plants

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