Fire,
Год журнала:
2024,
Номер
7(11), С. 412 - 412
Опубликована: Ноя. 12, 2024
Wildfires
occur
frequently
in
various
regions
of
the
world,
causing
serious
damage
to
natural
and
human
resources.
Traditional
wildfire
prevention
management
methods
are
often
hampered
by
monitoring
challenges
low
efficiency.
Digital
twin
technology,
as
a
highly
integrated
virtual
simulation
model,
shows
great
potential
prevention.
At
same
time,
virtual–reality
combination
digital
technology
can
provide
new
solutions
for
management.
This
paper
summarizes
key
technologies
required
establish
system,
focusing
on
technical
requirements
research
progress
fire
detection,
simulation,
prediction.
also
proposes
(WFDT)
which
integrates
real-time
data
computational
simulations
replicate
predict
behavior.
The
synthesis
these
techniques
within
framework
offers
comprehensive
approach
management,
providing
critical
insights
decision-makers
mitigate
risks
improve
emergency
response
strategies.
Energies,
Год журнала:
2024,
Номер
17(13), С. 3295 - 3295
Опубликована: Июль 4, 2024
Achieving
sustainable
green
building
design
is
essential
to
reducing
our
environmental
impact
and
enhancing
energy
efficiency.
Traditional
methods
often
depend
heavily
on
expert
knowledge
subjective
decisions,
posing
significant
challenges.
This
research
addresses
these
issues
by
introducing
an
innovative
framework
that
integrates
information
modeling
(BIM),
explainable
artificial
intelligence
(AI),
multi-objective
optimization.
The
includes
three
main
components:
data
generation
through
DesignBuilder
simulation,
a
BO-LGBM
(Bayesian
optimization–LightGBM)
predictive
model
with
LIME
(Local
Interpretable
Model-agnostic
Explanations)
for
prediction
interpretation,
the
optimization
technique
AGE-MOEA
address
uncertainties.
A
case
study
demonstrates
framework’s
effectiveness,
achieving
high
accuracy
(R-squared
>
93.4%,
MAPE
<
2.13%)
identifying
HVAC
system
features.
resulted
in
13.43%
improvement
consumption,
CO2
emissions,
thermal
comfort,
additional
4.0%
gain
when
incorporating
enhances
transparency
of
machine
learning
predictions
efficiently
identifies
optimal
passive
active
solutions,
contributing
significantly
construction
practices.
Future
should
focus
validating
its
real-world
applicability,
assessing
generalizability
across
various
types,
integrating
generative
capabilities
automated
Future Generation Computer Systems,
Год журнала:
2024,
Номер
155, С. 146 - 163
Опубликована: Фев. 13, 2024
Wetlands
play
a
critical
role
in
maintaining
the
global
climate,
regulating
hydrological
cycle,
and
protecting
human
health.
However,
they
are
rapidly
disappearing
due
to
activities.
Waterbirds
valuable
bio-indicators
of
wetland
health,
but
it
is
challenging
monitor
them
effectively.
Wireless
Multimedia
Sensor
Networks
(WMSNs)
offer
promising
technology
for
monitoring
wetlands.
Nonetheless,
these
networks
constrained
terms
energy,
also
encounter
challenges
associated
with
large-scale
deployments
under
natural
environmental
conditions.
These
conditions
introduce
harsh
circumstances
that
may
not
have
been
anticipated
during
pre-deployment
testing
phase.
This
paper
proposes
Digital
Twin
(DT)
based
energy-efficient
WMSN
system
specifically
tailored
waterbirds
The
utilizes
unique
approach
combines
local
audio
identification
image
compression
DT
optimize
network
performance
minimize
energy
consumption.
To
reduce
unnecessary
transmissions,
employs
real-time,
low-complexity
phase
before
triggering
capture.
A
denoising
step
employed
achieve
highly
accurate
bird
recognition
despite
surrounding
noises.
Each
undergoes
scheme
prior
transmission,
further
enhancing
efficiency.
enhance
system's
overall
efficiency
effectiveness,
integrated
create
real-time
replicas
application.
synergistic
interaction
between
two
DTs
enables
cooperative
data-making
decision
ensures
both
QoS
(Quality
Service)
QoE
Experience)
requirements
met.
Transmission
rate
control
done
using
fuzzy
logic
decision-making
technique.
Real-time
feedback
provides
rapid
analysis
current
state
WMSN,
allowing
dynamic
adjustments.
"what-if
scenarios"
feature
implemented
has
effectively
leveraged
find
most
suitable
settings
controller.
effectiveness
enhancements
achieved
by
integrating
into
our
WMSN-based
surveillance
validated
through
comprehensive
experiments
scenarios
correspond
real-world
wetland.
Comparative
analyses
demonstrate
undeniable
benefits
DT-integrated
compared
conventional
setup.
In
particular,
results
superior
efficiency,
capabilities,
ability
handle
multiple
video
sources.
IET Wireless Sensor Systems,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 3, 2024
Abstract
The
integration
of
digital
twins
(DTs)
in
healthcare
is
critical
but
remains
limited
real‐time
patient
monitoring
due
to
challenges
achieving
low‐latency
telemetry
transmission
and
efficient
resource
management.
This
paper
addresses
these
limitations
by
presenting
a
novel
cloud‐based
DT
framework
that
optimises
monitoring,
providing
timely
solution
for
needs.
incorporates
Pyomo‐based
dynamic
optimisation
model,
which
reduces
latency
32%
improves
response
time
52%,
surpassing
existing
systems.
Leveraging
low‐cost,
multimodal
sensors,
the
system
continuously
monitors
physiological
parameters,
including
SpO2,
heart
rate,
body
temperature,
enabling
proactive
health
interventions.
A
definition
language
(Digital
Twin
Definition
Language)‐based
series
analysis
twin
graph
platform
further
enhance
sensor
connectivity
scalability.
Additionally,
machine
learning
(ML)
strengthens
predictive
accuracy,
98%
accuracy
99.58%
under
cross‐validation
(cv
=
20)
using
XGBoost
algorithm.
Empirical
results
demonstrate
substantial
improvements
processing
time,
stability,
capacity,
with
predictions
completed
17
ms.
represents
significant
advancement
offering
responsive
scalable
constraints
applications.
Future
research
could
explore
incorporating
additional
sensors
advanced
ML
models
expand
its
impact
Journal of Civil Engineering and Management,
Год журнала:
2025,
Номер
31(4), С. 395 - 417
Опубликована: Апрель 29, 2025
This
paper
examines
the
role
of
Digital
Twin
Technology
(DTT)
in
transforming
infrastructure
management,
with
a
focus
on
sustainability.
It
highlights
how
advancements
Artificial
Intelligence
(AI),
Building
Information
Modeling
(BIM),
and
Internet
Things
(IoT)
are
driving
effectiveness
Twins
real-world
applications.
Through
detailed
case
studies,
showcases
practical
benefits
DTT
across
various
sectors.
also
evaluates
current
trends
strategies
for
enhancing
integration
into
systems.
The
research
reveals
striking
80%
increase
DTT-related
publications
from
2019
to
2024,
Asia,
particularly
China,
leading
contributions.
concludes
by
addressing
future
potential,
challenges,
risks
DTT,
offering
valuable
insights
stakeholders
aiming
optimize
management
digital
era.
