International Journal of Network Security & Its Applications,
Год журнала:
2024,
Номер
16(3), С. 01 - 21
Опубликована: Май 29, 2024
The
smart
irrigation
system
represents
an
innovative
approach
to
optimize
water
usage
in
agricultural
and
landscaping
practices.
integration
of
cutting-edge
technologies,
including
sensors,
actuators,
data
analysis,
empowers
this
provide
accurate
monitoring
control
processes
by
leveraging
real-time
environmental
conditions.
main
objective
a
is
efficiency,
minimize
expenses,
foster
the
adoption
sustainable
management
methods.
This
paper
conducts
systematic
risk
assessment
exploring
key
components/assets
their
functionalities
system.
crucial
role
sensors
gathering
on
soil
moisture,
weather
patterns,
plant
well-being
emphasized
These
enable
intelligent
decision-making
scheduling
distribution,
leading
enhanced
efficiency
Actuators
automated
devices,
ensuring
precise
targeted
delivery
plants.
Additionally,
addresses
potential
threat
vulnerabilities
associated
with
systems.
It
discusses
limitations
system,
such
as
power
constraints
computational
capabilities,
calculates
security
risks.
suggests
possible
treatment
methods
for
effective
secure
operation.
In
conclusion,
emphasizes
significant
benefits
implementing
systems,
improved
conservation,
increased
crop
yield,
reduced
impact.
based
analysis
conducted,
recommends
implementation
countermeasures
approaches
address
ensure
integrity
reliability
By
incorporating
these
measures,
technology
can
revolutionize
practices
agriculture,
promoting
sustainability,
resource
safeguarding
against
threats.
Environmental Chemistry Letters,
Год журнала:
2024,
Номер
22(5), С. 2293 - 2318
Опубликована: Май 21, 2024
Abstract
The
access
to
clean
and
drinkable
water
is
becoming
one
of
the
major
health
issues
because
most
natural
waters
are
now
polluted
in
context
rapid
industrialization
urbanization.
Moreover,
pollutants
such
as
antibiotics
escape
conventional
wastewater
treatments
thus
discharged
ecosystems,
requiring
advanced
techniques
for
treatment.
Here
we
review
use
artificial
intelligence
machine
learning
optimize
pharmaceutical
treatment
systems,
with
focus
on
quality,
disinfection,
renewable
energy,
biological
treatment,
blockchain
technology,
algorithms,
big
data,
cyber-physical
automated
smart
grid
power
distribution
networks.
Artificial
allows
monitoring
contaminants,
facilitating
data
analysis,
diagnosing
easing
autonomous
decision-making,
predicting
process
parameters.
We
discuss
advances
technical
reliability,
energy
resources
management,
cyber-resilience,
security
functionalities,
robust
multidimensional
performance
platform
distributed
consortium,
stabilization
abnormal
fluctuations
quality
Abstract
With
the
advancement
of
digital
technologies,
creation
a
twin
road
has
moved
from
theoretical
concept
to
tangible
reality.
Digital
twins
enable
rapid
simulations
and
robust
data
management,
thereby
ostensibly
empowering
policymakers
engineers
make
expeditious
well-informed
decisions.
This
paper
examines
potential
applications,
benefits,
implications
deploying
road,
real-time
virtual
replica
physical
infrastructure,
four
critical
perspectives:
modelling
numerical
simulations,
law,
sustainability
assessment.
explores
offer
advancements
in
efficiency
infrastructure.
By
enabling
comprehensive
monitoring
optimisation,
facilitates
applications
sustainable
design,
predictive
maintenance,
efficient
operation.
Real-time
collection
analysis
could
allow
for
proactive
maintenance
better
resource
while
integration
advanced
materials
sensor
technologies
can
enhance
durability
performance.
Additionally,
support
holistic
life
cycle
approach,
facilitating
decision-making
planning
future
infrastructure
projects,
with
contribute
smarter
more
transportation
networks.
The
implementation
roads,
however,
faces
several
challenges
raises
numerous
concerns.
Key
issues
include
diverse
sources,
ensuring
accuracy
reliability,
addressing
protection
security
concerns,
requiring
legal
regulatory
frameworks
manage
protect
personal
data.
Journal of Applied Mathematics,
Год журнала:
2025,
Номер
2025(1)
Опубликована: Янв. 1, 2025
We
propose
a
unified
numerical
framework
for
the
transport
of
passive
pollutants
by
shallow‐water
flows.
The
mathematical
model
we
consider
describing
this
phenomenon
results
in
coupling
hydrodynamic
equations
with
two‐dimensional
advection–diffusion
equation
governing
pollutant
transport.
implementation
hyperbolic
model,
based
on
finite
element
method,
is
achieved
using
multiphysics
modeling
and
simulation
toolbox
featured
Feel++,
versatile
C++
library
applying
Galerkin
methods
solving
partial
differential
equations.
Numerical
experiments
targeted
arsenic,
cadmium,
lead,
heavy
metals
among
most
harmful
to
human
health,
are
presented
as
part
practical
application
Niger
River
Bamako.
validated
basis
RMSE
MAE
metrics,
some
commonly
used
error
measures
linear
regression,
observational
data.
These
indicators,
estimated
below
5%
observed
mean
value,
support
reliability
accuracy
capturing
dynamics
under
flow
conditions.
highlight
predictive
effectiveness
provide
better
insight
into
pollution
patterns
scrutinized
river
section.
International Journal of Environmental Research and Public Health,
Год журнала:
2023,
Номер
20(13), С. 6216 - 6216
Опубликована: Июнь 24, 2023
In
this
study,
machine
learning
models
were
implemented
to
predict
the
classification
of
coastal
waters
in
region
Eastern
Macedonia
and
Thrace
(EMT)
concerning
Escherichia
coli
(E.
coli)
concentration
weather
variables
framework
Directive
2006/7/EC.
Six
sampling
stations
EMT,
located
on
beaches
regional
units
Kavala,
Xanthi,
Rhodopi,
Evros,
Thasos
Samothraki,
selected.
All
1039
samples
collected
from
May
September
within
a
14-year
follow-up
period
(2009–2021).
The
parameters
acquired
nearby
meteorological
stations.
analysed
according
ISO
9308-1
for
detection
enumeration
E.
coli.
vast
majority
fall
into
category
1
(Excellent),
which
is
mark
high
quality
EMT.
experimental
results
disclose,
additionally,
that
two-class
classifiers,
namely
Decision
Forest,
Jungle
Boosted
Tree,
achieved
Accuracy
scores
over
99%.
addition,
comparing
our
performance
metrics
with
those
other
researchers,
diversity
observed
using
algorithms
water
prediction,
such
as
Artificial
Neural
Networks
Bayesian
Belief
demonstrating
satisfactory
results.
Machine
approaches
can
provide
critical
information
about
dynamic
contamination
and,
concurrently,
consider
classification.
Advances in civil and industrial engineering book series,
Год журнала:
2024,
Номер
unknown, С. 87 - 107
Опубликована: Июнь 28, 2024
Caribbean
islands
are
some
of
the
most
vulnerable
countries
in
world
to
experience
extreme
flooding
resulting
from
tropical
cyclones,
storm
surges,
and
excessive
rainfall.
Persistent
changes
global
climate
have
made
like
Trinidad
Tobago
hot
spots
change.
As
a
result,
occurrence
events
is
likely
persist
worse
by
barriers
adaptation
mitigation,
such
as
having
limited
knowledge
change
how
plan
for
its
impact
at
individual
level,
well
financial
resources
technical
know-how.
Using
secondary
research
methodology,
this
chapter
seeks
investigate
role
that
artificial
intelligence
(AI)
plays
urban
planning
design
responding
Tobago.
This
discusses
not
only
historical
events,
causes,
but
also
possible
use
integration
AI
spaces
can
assist
reducing
ill
effects
events.
