Sustainability,
Год журнала:
2022,
Номер
14(20), С. 13384 - 13384
Опубликована: Окт. 17, 2022
Water
management
is
one
of
the
crucial
topics
discussed
in
most
international
forums.
harvesting
and
recycling
are
major
requirements
to
meet
global
upcoming
demand
water
crisis,
which
prevalent.
To
achieve
this,
we
need
more
emphasis
on
techniques
that
applied
across
various
categories
applications.
Keeping
mind
population
density
index,
there
a
dire
implement
intelligent
mechanisms
for
effective
distribution,
conservation
maintain
quality
standards
purposes.
The
prescribed
work
discusses
about
few
areas
applications
required
efficient
management.
Those
recent
trends
wastewater
recycle,
rainwater
irrigation
using
Artificial
Intelligence
(AI)
models.
data
acquired
these
purely
unique
also
differs
by
type.
Hence,
use
model
or
algorithm
can
be
provide
solutions
all
Deep
Learning
(DL)
along
with
Internet
things
(IoT)
framework
facilitate
designing
smart
system
sustainable
usage
from
natural
resources.
This
surveys
AI/DL
IoT
network
case
studies,
sample
statistical
analysis
develop
an
framework.
Sustainability,
Год журнала:
2023,
Номер
15(18), С. 13557 - 13557
Опубликована: Сен. 11, 2023
In
recent
years,
artificial
intelligence
(AI),
as
a
rapidly
developing
and
powerful
tool
to
solve
practical
problems,
has
attracted
much
attention
been
widely
used
in
various
areas.
Owing
their
strong
learning
accurate
prediction
abilities,
all
sorts
of
AI
models
have
also
applied
wastewater
treatment
(WWT)
optimize
the
process,
predict
efficiency
evaluate
performance,
so
explore
more
cost-effective
solutions
WWT.
this
review,
we
summarize
analyze
applications
Specifically,
briefly
introduce
commonly
purposes,
advantages
disadvantages,
comprehensively
review
inputs,
outputs,
objectives
major
findings
particular
water
quality
monitoring,
laboratory-scale
research
process
design.
Although
gained
great
success
WWT-related
fields,
there
are
some
challenges
limitations
that
hinder
widespread
real
WWT,
such
low
interpretability,
poor
model
reproducibility
big
data
demand,
well
lack
physical
significance,
mechanism
explanation,
academic
transparency
fair
comparison.
To
overcome
these
hurdles
successfully
apply
make
recommendations
discuss
future
directions
applications.
