Energies,
Journal Year:
2024,
Volume and Issue:
17(17), P. 4277 - 4277
Published: Aug. 27, 2024
Despite
the
tightening
of
energy
performance
standards
for
buildings
in
various
countries
and
increased
use
efficient
renewable
technologies,
it
is
clear
that
sector
needs
to
change
more
rapidly
meet
Net
Zero
Emissions
(NZE)
scenario
by
2050.
One
problems
have
been
analyzed
intensively
recent
years
operation
much
than
they
were
designed
to.
This
problem,
known
as
gap,
found
many
often
attributed
poor
management
building
systems.
The
application
Artificial
Intelligence
(AI)
Building
Energy
Management
Systems
(BEMS)
has
untapped
potential
address
this
problem
lead
sustainable
buildings.
paper
reviews
different
AI-based
models
proposed
applications
with
intention
reduce
consumption.
It
compares
evaluated
reviewed
papers
presenting
accuracy
error
rates
model
identifies
where
greatest
savings
could
be
achieved,
what
extent.
review
showed
offices
(up
37%)
when
employ
AI
HVAC
control
optimization.
In
residential
educational
buildings,
lower
intelligence
existing
BEMS
results
smaller
23%
21%,
respectively).
Energies,
Journal Year:
2023,
Volume and Issue:
16(6), P. 2636 - 2636
Published: March 10, 2023
The
normal
development
of
“smart
buildings,”
which
calls
for
integrating
sensors,
rich
data,
and
artificial
intelligence
(AI)
simulation
models,
promises
to
usher
in
a
new
era
architectural
concepts.
AI
models
can
improve
home
functions
users’
comfort
significantly
cut
energy
consumption
through
better
control,
increased
reliability,
automation.
This
article
highlights
the
potential
using
design
functionality
smart
houses,
especially
implementing
living
spaces.
case
study
provides
examples
how
be
embedded
homes
user
experience
optimize
efficiency.
Next,
will
explore
thoroughly
analyze
thorough
analysis
current
research
on
use
technology
variety
innovative
ideas,
including
interior
Smart
Building
System
Framework
based
digital
twins
(DT).
Finally,
explores
advantages
homes,
emphasizing
Through
study,
theme
seeks
provide
ideas
effectively
functionality,
convenience,
overarching
goal
is
harness
by
transforming
we
live
our
improving
quality
life.
concludes
discussing
unresolved
issues
future
areas
usage
houses.
Incorporating
into
benefits
homeowners,
providing
excellent
safety
convenience
Sustainability,
Journal Year:
2023,
Volume and Issue:
15(6), P. 4955 - 4955
Published: March 10, 2023
Artificial
Intelligence
(AI)
simulation
models
and
digital
twins
(DT)
are
used
in
designing
treating
the
activities,
layout,
functions
for
new
generation
of
buildings
to
enhance
user
experience
optimize
building
performance.
These
use
data
about
a
building’s
use,
configuration,
functions,
environment
simulate
different
design
options
predict
their
effects
on
house
function
efficiency,
comfort,
safety.
On
one
hand,
AI
algorithms
analyze
this
find
patterns
trends
that
can
guide
process.
other
DTs
recreations
actual
structures
replicate
performance
real
time.
would
evaluate
alternative
options,
building,
ways
improve
comfort
efficiency.
This
study
examined
important
role
intelligent
aspects,
such
as
activities
using
multi-layout
creation
particular
based
models,
developing
DT-based
smart
systems.
The
empirical
came
from
architecture
engineering
firms
throughout
globe
CSAQ
(computer-administered,
self-completed
survey).
For
purpose,
employed
structural
equation
modeling
(SEM)
examine
hypotheses
build
relationship
model.
research
verifies
relevance
AI-based
supporting
features
(activities,
functionalities),
enabling
construction
Furthermore,
highlights
need
further
exploration
models’
integration
with
DT
design.
Architectural Science Review,
Journal Year:
2023,
Volume and Issue:
67(3), P. 237 - 254
Published: Aug. 3, 2023
AbstractThe
main
purpose
of
this
study
is
to
provide
insight
into
the
trend
AI-BIM
integration,
which
has
been
studied
by
scholars
around
world.
To
begin,
a
systematic
review
and
bibliometric
analysis
was
conducted
investigate
English
articles
published
between
2015
2022.
This
paper
presents
systematic,
scientometric,
science
mapping
through
qualitative
quantitative
evaluation
co-occurrence
methods
using
VOSviewer,
CiteSpace,
Gephi
software.
Conclusions
indicate
future
research
should
concentrate
on
integrating
AI
other
smart
systems
with
BIM
enhance
digitalization
improve
outcomes
throughout
construction
project
life
cycle.
Based
each
scope
(BIM
AI)
their
status
quo,
suggests
following
domains
reduce
complexity
in
industry
future:
robotics,
cloud
systems,
AIOT,
digital
twins,
4D
printing,
block
chain.KEYWORDS:
Building
information
modeling
(BIM)artificial
intelligence
(AI)construction
industrysmart
buildinginteroperabilitysystematic
literature
(SLR)
Disclosure
statementNo
potential
conflict
interest
reported
author(s).Data
availability
statementData
available
request
from
authors.
The
data
that
support
findings
are
corresponding
author,
[author
initials],
upon
reasonable
request.
All
software
files
used
available.
Energies,
Journal Year:
2024,
Volume and Issue:
17(13), P. 3295 - 3295
Published: July 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
Energies,
Journal Year:
2024,
Volume and Issue:
17(17), P. 4277 - 4277
Published: Aug. 27, 2024
Despite
the
tightening
of
energy
performance
standards
for
buildings
in
various
countries
and
increased
use
efficient
renewable
technologies,
it
is
clear
that
sector
needs
to
change
more
rapidly
meet
Net
Zero
Emissions
(NZE)
scenario
by
2050.
One
problems
have
been
analyzed
intensively
recent
years
operation
much
than
they
were
designed
to.
This
problem,
known
as
gap,
found
many
often
attributed
poor
management
building
systems.
The
application
Artificial
Intelligence
(AI)
Building
Energy
Management
Systems
(BEMS)
has
untapped
potential
address
this
problem
lead
sustainable
buildings.
paper
reviews
different
AI-based
models
proposed
applications
with
intention
reduce
consumption.
It
compares
evaluated
reviewed
papers
presenting
accuracy
error
rates
model
identifies
where
greatest
savings
could
be
achieved,
what
extent.
review
showed
offices
(up
37%)
when
employ
AI
HVAC
control
optimization.
In
residential
educational
buildings,
lower
intelligence
existing
BEMS
results
smaller
23%
21%,
respectively).
