smart water
How much should the water industry trust
artificial intelligence? Chaim Kolominskas, Manager EVS Water, Envirosuite
Deterministic and AI learning approaches should be used together as the industry continues along its journey of digitalisation.
to run tests, or run offline simulations or
I
studies. This is slow and impractical. Leaders in the sector are looking to alter-
dentification and interpretation
augmented with sensors that collect data to
native options such as digital twin technology
of patterns and relationships
support control of the process.
as a way of creating a virtual representation
in the vast amounts of data
As engineers and plant managers, we
of their operations, where changes can be
collected by water utilities has
know and trust deterministic models. These
simulated — and implications understood
the potential to drive better
models have proven reliable over the years
— quickly and with no impact to business-
operating decisions and drive reductions in
to represent and simulate processes such
as-usual operations. Automated deterministic
cost; however, engineers and decision-makers
as chemical reactions in drinking water
models, connected in near real time, are ideal
are sceptical of using artificial intelligence
or industrial wastewater treatment. If the
for this purpose, but they are reactive and
(AI) or machine learning (ML) as standalone
inputs into a process are known, the model
cannot deliver useful projections on what
approaches.
can produce a set of outputs that we use
you should do to avoid an issue.
to make decisions. It’s accepted that best
Hybrid approaches that combine deter-
as ‘black boxes’ that produce non-transparent,
practice models can represent a process
ministic and AI approaches can overcome
unexplainable outcomes and require constant
accurately enough to be used to understand
the limitations of both methods. Deterministic
oversight and supervision. Large amounts of
the implications of changes to the process.
modelling can be used to represent total
clean, historical and granular data are needed
However, these approaches are manual and
process performance, grounded in accepted
to be accurate. More importantly, experienced
traditionally require substantial technical
science of the industry with AI used to drive
operators and practitioners in the industry see
expertise to drive. Deterministic models are
accurate forecasts and recommendations for
the lack of connection to the industry itself as
also by their very nature not conducive to
short-term actions to improve performance.
a weakness. An ML model on its own does
forecasting.
Keeping personnel involved to oversee and im-
Algorithms are often presented and sold
plement recommendations remains important
not care about the industry that it is applied
The water industry needs to change
to and makes no connection to the accepted
to meet increasingly stringent operational,
physics, chemistry and biology of the process.
regulatory and environmental requirements,
At Envirosuite, we see the value in both
How should the water industry realise the
as well as the needs of surrounding com-
deterministic and AI learning approaches and
benefits that AI can deliver, while managing
munities. Understanding the implications of
believe that they should be used together as
the risks that come with the approach?
while trust is built in the system.
what doing something different would look
the industry continues along its journey of digi-
Digitalisation is driving change in the water
like is, however, a key challenge still fac-
talisation. As approaches evolve and improve,
and wastewater treatment sectors, just as it
ing water utilities. It is currently difficult to
we look forward to the further opportunities
is in other industrial and corporate environ-
measure or understand the applicability of
that AI could deliver to the water industry,
ments. Water and wastewater treatment plants
alternative operating scenarios. Operators
as long as we keep the humans in the loop.
collect more data than ever before. Control
and engineers must either live test and see
Envirosuite Operations Pty Ltd
and treatment equipment is increasingly
what happens, take part of the plant offline
https://envirosuite.com/platforms/water
This issue is sponsored by — Schneider Electric — se.com/au/getreadyformore 17