IGI Global eBooks,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 26
Published: Feb. 7, 2025
Climate
change
and
the
rapid
depletion
of
natural
resources
present
significant
global
challenges
that
demand
innovative
sustainable
solutions.
Traditional
resource
management
approaches
are
increasingly
inadequate
in
addressing
these
complexities,
creating
a
pressing
need
for
advanced
technologies.
Artificial
Intelligence
(AI)
Data
Science
have
emerged
as
powerful
tools
to
revolutionize
green
technologies,
enhancing
their
efficiency
effectiveness
promoting
sustainability.
This
chapter
provides
comprehensive
exploration
applications
AI
discussing
potential
impacts,
challenges,
ethical
considerations.
By
examining
aspects,
aims
illuminate
how
technologies
can
be
harnessed
address
environmental
support
future.
Sustainability,
Journal Year:
2023,
Volume and Issue:
15(18), P. 13557 - 13557
Published: Sept. 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.
Artificial Intelligence in Agriculture,
Journal Year:
2024,
Volume and Issue:
12, P. 72 - 84
Published: April 30, 2024
The
issue
of
food
security
continues
to
be
a
prominent
global
concern,
affecting
significant
number
individuals
who
experience
the
adverse
effects
hunger
and
malnutrition.
finding
solution
this
intricate
necessitates
implementation
novel
paradigm-shifting
methodologies
in
agriculture
sector.
In
recent
times,
domain
artificial
intelligence
(AI)
has
emerged
as
potent
tool
capable
instigating
profound
influence
on
sectors.
AI
technologies
provide
advantages
by
optimizing
crop
cultivation
practices,
enabling
use
predictive
modelling
precision
techniques,
aiding
efficient
monitoring
disease
identification.
Additionally,
potential
optimize
supply
chain
operations,
storage
management,
transportation
systems,
quality
assurance
processes.
It
also
tackles
problem
loss
waste
through
post-harvest
reduction,
analytics,
smart
inventory
management.
This
study
highlights
that
how
utilizing
power
AI,
we
could
transform
way
produce,
distribute,
manage
food,
ultimately
creating
more
secure
sustainable
future
for
all.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: March 29, 2024
Abstract
The
consumption
of
water
constitutes
the
physical
health
most
living
species
and
hence
management
its
purity
quality
is
extremely
essential
as
contaminated
has
to
potential
create
adverse
environmental
consequences.
This
creates
dire
necessity
measure,
control
monitor
water.
primary
contaminant
present
in
Total
Dissolved
Solids
(TDS),
which
hard
filter
out.
There
are
various
substances
apart
from
mere
solids
such
potassium,
sodium,
chlorides,
lead,
nitrate,
cadmium,
arsenic
other
pollutants.
proposed
work
aims
provide
automation
estimation
through
Artificial
Intelligence
uses
Explainable
(XAI)
for
explanation
significant
parameters
contributing
towards
potability
impurities.
XAI
transparency
justifiability
a
white-box
model
since
Machine
Learning
(ML)
black-box
unable
describe
reasoning
behind
ML
classification.
models
Logistic
Regression,
Support
Vector
(SVM),
Gaussian
Naive
Bayes,
Decision
Tree
(DT)
Random
Forest
(RF)
classify
whether
drinkable.
representations
force
plot,
test
patch,
summary
dependency
plot
decision
generated
SHAPELY
explainer
explain
features,
prediction
score,
feature
importance
justification
estimation.
RF
classifier
selected
yields
optimum
Accuracy
F1-Score
0.9999,
with
Precision
Re-call
0.9997
0.998
respectively.
Thus,
an
exploratory
analysis
indicators
associated
their
significance.
emerging
research
at
vision
addressing
future
well.
AgriEngineering,
Journal Year:
2024,
Volume and Issue:
6(2), P. 1479 - 1496
Published: May 28, 2024
The
livestock
industry
is
undergoing
significant
transformation
with
the
integration
of
intelligent
technologies
aimed
at
enhancing
productivity,
welfare,
and
sustainability.
This
review
explores
latest
advancements
in
systemization
(IS),
including
real-time
monitoring,
machine
learning
(ML),
Internet
Things
(IoT),
their
impacts
on
farming.
aim
this
study
to
provide
a
comprehensive
overview
how
these
can
address
challenges
by
improving
animal
health,
optimizing
resource
use,
promoting
sustainable
practices.
methods
involve
an
extensive
current
literature
case
studies
data
analytics,
automation
feeding
climate
control,
renewable
energy
integration.
results
indicate
that
IS
enhances
well-being
through
health
monitoring
early
disease
detection,
optimizes
efficiency,
reduces
operational
costs
automation.
Furthermore,
contribute
environmental
sustainability
minimizing
waste
reducing
ecological
footprint
highlights
transformative
potential
creating
more
efficient,
humane,
industry.
Water,
Journal Year:
2023,
Volume and Issue:
15(9), P. 1750 - 1750
Published: May 2, 2023
Developing
precise
soft
computing
methods
for
groundwater
management,
which
includes
quality
and
quantity,
is
crucial
improving
water
resources
planning
management.
In
the
past
20
years,
significant
progress
has
been
made
in
management
using
hybrid
machine
learning
(ML)
models
as
artificial
intelligence
(AI).
Although
various
review
articles
have
reported
advances
this
field,
existing
literature
must
cover
ML.
This
article
aims
to
understand
current
state-of-the-art
ML
used
achievements
domain.
It
most
cited
employed
from
2009
2022.
summarises
reviewed
papers,
highlighting
their
strengths
weaknesses,
performance
criteria
employed,
highly
identified.
worth
noting
that
accuracy
was
significantly
enhanced,
resulting
a
substantial
improvement
demonstrating
robust
outcome.
Additionally,
outlines
recommendations
future
research
directions
enhance
of
including
prediction
related
knowledge.
Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
34(48)
Published: July 1, 2024
Abstract
Fog
harvest
has
emerged
as
a
direct
and
efficient
water
harvesting
technology
to
relieve
the
intense
pressure
of
freshwater
scarcity
worldwide.
With
vagaries
climate
increasing
amount
energy
consumption,
high‐efficiency
fog
devices
focus
on
fast
droplet
capture
transportation
are
highly
desired.
In
this
study,
novel
harp
structure
is
developed
using
cross‐twisted
copper
filaments
arranged
in
spatial
triangular
pattern
enhance
transportation.
Inspired
by
natural
differences
Laplace
observed
cactus
spider
silks,
design
accelerates
movement
bridges.
Besides,
drawing
fruit
waxes
surface
hogweed
blueberries,
paraffin
wax
coating
applied
sheet
frame
create
solid
slip
frame,
improving
synergy
between
filament
The
monolithic
collector
(MFC)
thus
achieves
significant
increase
efficiency
demonstrates
excellent
durability.
Integration
MFCs
into
3D
system
results
rate
0.5027
g
cm
−2
min
−1
,
showing
promise
for
practical
applications
due
its
durability,
simplicity,
environmental
friendliness.
International Journal of Science and Research Archive,
Journal Year:
2024,
Volume and Issue:
11(1), P. 502 - 512
Published: Jan. 26, 2024
The
integration
of
Artificial
Intelligence
(AI)
in
groundwater
management
is
a
transformative
stage,
characterized
by
innovation
and
challenges.
This
research
paper
explores
the
multilayered
application
AI
this
field,
dividing
its
contributions,
addressing
associated
challenges,
revealing
prospects
future
potential.
AI-driven
innovations
are
designed
to
revolutionize
management,
providing
precise
predictive
modeling,
real-time
monitoring,
data
integration.
However,
these
face
challenges
such
as
interpretability
issues,
specialized
technical
expertise
requirements,
limited
quality
quantity
for
effective
model
performance.
In
future,
holds
significant
promise
management.
Advanced
models
can
yield
improved
predictions
behavior,
identify
vulnerable
areas
prone
pollution
depletion,
prompt
proactive
interventions,
foster
collaborative
platforms
among
scientists,
policymakers,
local
communities.
Collaborative
driven
offer
potential
synergistic
engagement
communities,
collectively
guiding
resource
Embracing
AI's
while
remains
pivotal
sustainable
resilient
practices.
By
embracing
landscape
will
continue
evolve.
