• Research into the use of other (as opposed to the techniques used so far),
potentially more efficient, optimisation techniques to solve the sensor placement
for leak/burst detection and localisation problem should be carried out. This
research should favourably look into algorithms that are able to automatically
adjust their hyper-parameters and into the possibility of using parallel and high
performance computing.
• Further investigations into the potential of using clustering algorithms coupled
with optimisation techniques (as opposed to clustering algorithms used on their
own) to reduce the size of the solution space/complexity of the sensor placement
problem should be carried out.
• Tightly coupled optimal sensor placement and leak/burst localisation frameworks
should be developed by researchers in the future as an optimal placement depends
on the method that is used to localise the potential leaks/bursts and the efficiency
of the leak/burst localisation depends on the sensor placement.
• Much greater attention should be paid by researchers in the future to the issue of
sensor/communication failures as this is of critical importance for the effectiveness of optimal sensor placements for leak/burst detection and localisation.
Research into the use of artificial intelligence-type and (geo)statistical techniques
with the potential to mitigate this issue and issues related to the use of imperfect
hydraulic models should also be carried out.
• Methods for the optimal placement of pressure and flow sensors simultaneously
should also be the focus of further research and development in the future as using
additional flow instrumentation can improve the leak/burst detection and
localisation performance. In this context, the developed methods should carefully
account for cost-benefit considerations as, because of the higher costs associated
with obtaining flow measurements, including such considerations becomes even
more important than it currently is.
• Future optimal sensor placement methods should also account for risk in order to
be of even more value to water companies. Further research into refining the
means of estimating the likelihood and impact components of risk should be
carried out.
• Future optimal sensor placement studies should strive to incorporate results from
field demonstrations as this is the only way to ultimately assess the actual
capabilities of a proposed approach. Where this is not possible, future studies
should at least include an assessment of their underlying capabilities using a set of
common quantitative metrics, benchmark models and leak/burst scenarios.
Although optimal sampling design for leak/burst detection and localisation has
been the focus of this review, researchers and practitioners interested in this topic
should also look at macro-location of sensors in the wider context of WDSs
management (i.e. look at optimal sampling design techniques developed for the
numerous other optimisation agendas such as detection of contamination events).
56
M. Romano
potentially more efficient, optimisation techniques to solve the sensor placement
for leak/burst detection and localisation problem should be carried out. This
research should favourably look into algorithms that are able to automatically
adjust their hyper-parameters and into the possibility of using parallel and high
performance computing.
• Further investigations into the potential of using clustering algorithms coupled
with optimisation techniques (as opposed to clustering algorithms used on their
own) to reduce the size of the solution space/complexity of the sensor placement
problem should be carried out.
• Tightly coupled optimal sensor placement and leak/burst localisation frameworks
should be developed by researchers in the future as an optimal placement depends
on the method that is used to localise the potential leaks/bursts and the efficiency
of the leak/burst localisation depends on the sensor placement.
• Much greater attention should be paid by researchers in the future to the issue of
sensor/communication failures as this is of critical importance for the effectiveness of optimal sensor placements for leak/burst detection and localisation.
Research into the use of artificial intelligence-type and (geo)statistical techniques
with the potential to mitigate this issue and issues related to the use of imperfect
hydraulic models should also be carried out.
• Methods for the optimal placement of pressure and flow sensors simultaneously
should also be the focus of further research and development in the future as using
additional flow instrumentation can improve the leak/burst detection and
localisation performance. In this context, the developed methods should carefully
account for cost-benefit considerations as, because of the higher costs associated
with obtaining flow measurements, including such considerations becomes even
more important than it currently is.
• Future optimal sensor placement methods should also account for risk in order to
be of even more value to water companies. Further research into refining the
means of estimating the likelihood and impact components of risk should be
carried out.
• Future optimal sensor placement studies should strive to incorporate results from
field demonstrations as this is the only way to ultimately assess the actual
capabilities of a proposed approach. Where this is not possible, future studies
should at least include an assessment of their underlying capabilities using a set of
common quantitative metrics, benchmark models and leak/burst scenarios.
Although optimal sampling design for leak/burst detection and localisation has
been the focus of this review, researchers and practitioners interested in this topic
should also look at macro-location of sensors in the wider context of WDSs
management (i.e. look at optimal sampling design techniques developed for the
numerous other optimisation agendas such as detection of contamination events).
56
M. Romano