785
Views
31
CrossRef citations to date
0
Altmetric
Review Article

A state-of-the-art review of an optimal sensor placement for contaminant warning system in a water distribution network

ORCID Icon, ORCID Icon, & ORCID Icon
Pages 985-1000 | Received 18 Sep 2018, Accepted 15 Mar 2019, Published online: 19 Apr 2019
 

ABSTRACT

Protection of water distribution networks (WDNs) is at the forefront because of the negative implications of the use of the contaminated water on the public health. In order to safeguard the water distribution networks from accidental and intentional attacks, a water quality sensor should be installed across the network. Remarkably, the budget constraints to procure and maintain sensors have limited the number of sensors deployed in networks. These constraints make the optimal sensor placement receive notable attention. Over time, researchers have devised various methodologies to tackle sensor placement in a water distribution network. Investigations have shown that each of the methodologies has a research gap which must be addressed. In this work, a state-of-the-art review of optimal sensor placement in a water distribution network is presented. The review results show technical challenges, possible solutions, and future research directions in this domain.

Acknowledgements

The authors would like to thank the Tshwane University of Technology, and the French South African Institute of Technology (F’SATI), Pretoria, South Africa for their financial support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 239.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.