Buildings,
Journal Year:
2025,
Volume and Issue:
15(3), P. 498 - 498
Published: Feb. 5, 2025
Amid
global
efforts
to
mitigate
greenhouse
gas
emissions,
improving
the
energy
efficiency
of
buildings
has
emerged
as
a
strategic
priority.
Buildings
account
for
approximately
40%
consumption
and
significant
share
CO2
making
them
key
targets
sustainable
practices.
This
study
employs
systematic
literature
review
combined
with
bibliometric
analysis
explore
transformative
potential
digital
twins
in
building
efficiency.
The
synthesizes
contributions
real-time
monitoring,
predictive
modeling,
renewable
integration,
proactive
maintenance
while
addressing
critical
challenges
such
interoperability,
scalability,
privacy.
originality
this
work
lies
its
integrated
approach,
which
identifies
emerging
trends
research
gaps,
providing
actionable
insights
guide
future
adoption
sector.
These
findings
highlight
pivotal
role
fostering
intelligent
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: June 11, 2024
As
a
facilitator
of
smart
upgrading,
digital
twin
(DT)
is
emerging
as
driving
force
in
prognostics
and
health
management
(PHM).
Faults
can
lead
to
degradation
or
malfunction
industrial
assets.
Accordingly,
DT-driven
PHM
studies
are
conducted
improve
reliability
reduce
maintenance
costs
However,
there
lack
systematic
research
analyze
summarize
current
applications
methodologies
for
Therefore,
this
paper
first
analyzes
the
application
DT
from
field,
aspect,
hierarchy
at
layer.
The
next
deepens
into
core
mechanism
theory
Then
enabling
technologies
tools
modeling
system
investigated
summarized
implementation
Finally,
observations
future
suggestions
presented.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(21), P. 9275 - 9275
Published: Oct. 25, 2024
This
research
investigates
the
use
of
digital
twin
(DT)
technology
to
improve
building
energy
management
and
analyse
occupant
behaviour.
DTs
perform
function
acting
as
virtual
replicas
physical
assets,
which
facilitates
real-time
monitoring,
predictive
maintenance,
data-driven
decision-making.
Consequently,
performance
comfort
can
be
enhanced.
study
evaluates
efficiency
in
optimising
usage
by
a
mix
systematic
literature
review
scientometric
analysis
466
articles
from
Scopus
database.
Among
main
obstacles
noted
are
interoperability
issues,
privacy
data
quality
difficulties,
requirement
for
more
thorough
integration
interactions.
The
results
highlight
necessity
standardised
frameworks
direct
DT
implementations
suggest
areas
further
study,
especially
improving
cybersecurity
incorporating
behaviour
into
models.
makes
practical
recommendations
using
increase
sustainability
built
environment.
Optimization
and
proactive
management
of
energy
systems
are
crucial
for
achieving
sustainability,
efficiency
resilience
in
future
smart
networks.
Data-driven
approaches
offer
promising
solutions
tackling
the
complex
dynamic
challenges
systems,
such
as
uncertainty,
variability,
heterogeneity.
Meanwhile,
recent
advances
decreasing
hardware
costs
improving
data
accessibility
have
allowed
collection
high-quality
data,
leading
to
development
more
accurate
robust
data-driven
models
different
systems.
In
this
study,
a
comprehensive
overview
current
trends
optimization
is
presented.
After
introducing
motivation
background
research
field,
potential
applications
benefits
various
domains
discussed,
electric
vehicles
charge,
district
heating
networks
districts.
Subsequently
review
focuses
on
methods
techniques
management,
ranging
from
scientific
machine
learning
algorithms.
Finally,
novel
European
project,
DigiBUILD,
introduced,
where
case
studies
tested
several
pilots,
including
vehicle
charging
increasing
renewable
source
consumption,
network
operative
building
comfort
management.
Frontiers in Energy Research,
Journal Year:
2024,
Volume and Issue:
12
Published: Jan. 23, 2024
Intelligent
construction
is
a
necessary
way
to
improve
the
traditional
method,
and
digital
twin
can
be
crucial
technology
promote
intelligent
construction.
However,
field
currently
needs
unified
method
build
standardized
universally
applicable
model,
which
incredibly
challenging
in
Therefore,
this
paper
proposes
general
construct
process
model
based
on
Industry
Foundation
Classes
(IFC)
standard,
aiming
realize
real-time
monitoring,
control,
visualization
management
of
site.
The
constructs
fusion
from
three
levels:
geometric
resource
behavioral
by
establishing
an
IFC
semantic
process,
storing
data
site
into
database,
completing
dynamic
interaction
database.
At
same
time,
platform
developed
control
Combined
with
practical
cases
analysis,
implementation
effect
shown
verified.
results
show
that
adapt
itself
different
scenarios
site,
conducive
promoting
application
provides
reference
research
practicing
theory
practice.
Building Services Engineering Research and Technology,
Journal Year:
2024,
Volume and Issue:
45(4), P. 475 - 498
Published: March 21, 2024
Smart
buildings
and
cities
are
rapidly
emerging
as
solutions
to
address
the
challenges
of
efficiency,
urbanisation,
sustainability
in
sector.
The
study
proposes
deploying
data-driven
digital
twins
for
smart
by
utilising
available
building’s
technology
IT
infrastructure
complement
augment
existing
functions.
twin
will
consist
a
core
energy
model
2D
visual
representation
systems,
with
potential
future
evolution
into
3D
model.
This
aims
present
preliminary
investigation
idea
building
management
towards
enhancing
operations
empowering
concept
cities.
It
is
demonstrated
on
campus
Qatar
University.
With
an
emphasis
air
conditioning
systems
building,
considering
their
substantial
contribution
overall
consumption,
maintains
open
approach
also
encompass
other
within
buildings,
presents
comparative
evaluation
between
simulation-based
modelling
case
study,
well
exploration
various
machine
learning
algorithms
that
can
be
used.
Furthermore,
exploring
essential
applications
twin.
Practical
Application
provides
comprehensive
practical
aspects
addressing
related
data
collection,
development,
integration
infrastructure,
limitations.
paper
advance
field
facility
promote
sustainable
practices
operations.
By
contributing
knowledge
services
management,
our
offers
guidance
optimising
performance,
reducing
fostering
urban
development.
Frontiers in Built Environment,
Journal Year:
2024,
Volume and Issue:
10
Published: April 10, 2024
This
research
paper
explores
the
integration
of
novel
technologies
in
hospital
emergency
evacuations,
particularly
Operating
Rooms
(ORs)
and
Emergency
Departments
(EDs).
It
examines
application
advanced
tools
like
simulation
modeling,
Building
Information
Modeling
(BIM),
Digital
Twin
technology,
sensor
data,
Artificial
Intelligence
(AI)
to
improve
evacuation
strategies
building.
The
study
extends
in-depth
case
studies
for
assessing
practicality
existing
protocols,
while
also
highlighting
critical
importance
staff
training
preparedness.
Additionally,
it
addresses
ethical
psychological
impacts
emergencies
on
patients
healthcare
staff,
underscoring
need
technology
be
complemented
with
human-centered
care.
concludes
by
emphasizing
ongoing
necessity
innovative
enhancing
safety
operational
resilience
management.
Smart and Sustainable Built Environment,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Aug. 2, 2024
Purpose
Predictive
digital
twin
technology,
which
amalgamates
twins
(DT),
the
internet
of
Things
(IoT)
and
artificial
intelligence
(AI)
for
data
collection,
simulation
predictive
purposes,
has
demonstrated
its
effectiveness
across
a
wide
array
industries.
Nonetheless,
there
is
conspicuous
lack
comprehensive
research
in
built
environment
domain.
This
study
endeavours
to
fill
this
void
by
exploring
analysing
capabilities
individual
technologies
better
understand
develop
successful
integration
use
cases.
Design/methodology/approach
uses
mixed
literature
review
approach,
involves
using
bibliometric
techniques
as
well
thematic
critical
assessments
137
relevant
academic
papers.
Three
separate
lists
were
created
Scopus
database,
covering
AI
IoT,
DT,
since
IoT
are
crucial
creating
DT.
Clear
criteria
applied
create
three
lists,
including
limiting
results
only
Q1
journals
English
publications
from
2019
2023,
order
include
most
recent
highest
quality
publications.
The
collected
was
analysed
package
R
Studio.
Findings
reveal
asymmetric
attention
various
components
twin’s
system.
There
relatively
greater
body
on
representing
43
47%,
respectively.
In
contrast,
direct
net-zero
solutions
constitutes
10%.
Similarly,
findings
underscore
necessity
integrating
these
carbon
emission
prediction.
Practical
implications
indicate
that
clear
need
more
case
studies
investigating
large-scale
networks
collect
buildings
construction
sites.
Furthermore,
development
advanced
precise
models
imperative
predicting
production
renewable
energy
sources
demand
housing.
Originality/value
paper
makes
significant
contribution
field
providing
strong
theoretical
foundation.
It
also
serves
catalyst
future
within
For
practitioners
policymakers,
offers
reliable
point
reference.
