Buildings,
Journal Year:
2024,
Volume and Issue:
14(4), P. 1077 - 1077
Published: April 12, 2024
Shared
public
buildings
have
become
centers
of
innovation,
integrating
advanced
technologies
to
meet
evolving
societal
needs.
With
a
heightened
emphasis
on
occupants’
health
and
well-being,
these
serve
as
hubs
for
technological
convergence,
facilitating
seamless
connectivity
intelligent
data
analysis
management.
Within
this
context,
environmental
monitoring
emerges
foundational
element,
pivotal
all
aspects
building
This
article
provides
findings
from
the
nationally
funded
RE-START
project,
which
focuses
shared
buildings,
with
special
regard
educational
medical
facilities.
The
project
explores
enhanced
indoor
air
quality
monitoring,
focusing
CO2
concentration
that
is
directly
correlated
occupancy,
fundamental
element
developing
safety
protocols,
energy
efficiency
strategies,
integration
smart
technologies,
data-driven
intersection
efficiency,
security,
IoT
in
spaces
relevant.
outcomes
study
reveal
delicate
nature
involved
components,
need
be
carefully
developed
an
integrated
manner.
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.
Energy Exploration & Exploitation,
Journal Year:
2024,
Volume and Issue:
42(6), P. 2191 - 2217
Published: Aug. 2, 2024
Due
to
rising
demand
for
energy-efficient
buildings,
advanced
predictive
models
are
needed
evaluate
heating
and
cooling
load
requirements.
This
research
presents
a
unified
strategy
that
blends
LSTM
networks
GBM
improve
building
energy
estimates’
precision
reliability.
Data
on
usage,
weather
conditions,
occupancy
trends,
features
is
collected
prepared
start
the
process.
model
attributes
created
using
sequential
relationships
initial
projections
networks.
Combining
with
takes
advantage
of
each
model's
strengths:
LSTM's
data
processing
GBM's
complex
nonlinear
connection
capture.
Performance
measures
like
RMSE
MAE
used
hybrid
validity.
Compared
individual
models,
integrated
LSTM-GBM
method
improves
prediction
accuracy.
higher
capacity
allows
real-time
management
systems,
improving
operations
reducing
use.
Implementing
this
in
Building
Management
Systems
(BMS)
shows
its
practicality
achieving
sustainable
efficiency.
Frontiers in Built Environment,
Journal Year:
2025,
Volume and Issue:
11
Published: March 13, 2025
In
the
contemporary
digital
age,
built
environment
undergoes
significant
changes
because
of
technological
innovations
that
improve
building
management,
optimize
efficiency,
and
enhance
overall
productivity.
Digital
Twin
technology
has
emerged
as
an
indispensable
tool
for
enhancing
indoor
environmental
quality
optimizing
energy
efficiency
in
existing
buildings.
This
demonstrates
its
similarity
to
several
SDGs,
where
twin
is
key
achieving
many
them,
especially
those
relevant
our
research:
7.
Affordable
clean
energy;
3.
Good
health
wellbeing
are
primary
outcomes
study;
9.
Industry
innovation
infrastructure
focus
methodology;
11.
Sustainable
cities
communication,
which
research
contributes.
However,
some
challenges
require
further
consideration.
First,
assess
methods
tools
used
monitor
represent
parameters.
Second,
review
previous
studies
on
context
quality.
study
systematically
examined
261
academic
articles
address
these
challenges,
identifying
17
publications
investigating
The
emphasizes
Building
Information
Modeling,
Internet
Things,
Big
Data,
collectively
monitoring
management
physical
assets
through
real-time
data
replication.
Our
illustrates
need
a
multidisciplinary
framework
rigorously
analyze
applications,
comprehensive
understanding
consequences
this
requires
integration
different
fields.
confined
application
sensors
environment,
importance
residents
subjective
impressions,
comparative
use
estimation
methods.
For
future
investigation,
enhanced
international
collaboration
imperative
scholarly
exploration
related
field.
Finally,
can
benefit
significantly
from
implementing
technology.
must
be
addressed
before
achieve
full
potential
creating
sustainable
energy-efficient
Buildings,
Journal Year:
2025,
Volume and Issue:
15(7), P. 1030 - 1030
Published: March 24, 2025
Smart
buildings
equipped
with
diverse
control
systems
serve
the
objectives
of
gathering
data,
optimizing
energy
efficiency
(EE),
and
detecting
diagnosing
faults,
particularly
in
domain
indoor
environmental
quality
(IEQ).
Digital
twins
(DTs)
offering
an
environmentally
sustainable
solution
for
managing
facilities
incorporated
artificial
intelligence
(AI)
create
opportunities
maintaining
IEQ
EE.
The
purpose
this
study
is
to
assess
impact
AI-driven
DTs
on
enhancing
EE
smart
building
(SBS).
A
scoping
review
was
performed
establish
theoretical
background
about
DTs,
AI,
IEQ,
SBS,
semi-structured
interviews
were
conducted
specialists
industry
obtain
qualitative
quantitative
data
gathered
via
a
computerized
self-administered
questionnaire
(CSAQ)
survey,
focusing
how
can
improve
SBS.
results
indicate
that
DT
enhances
occupants’
comfort
energy-efficiency
performance
enables
decision-making
automatic
fault
detection
maintenance
conditioning
buildings’
serviceability
real
time,
response
key
industrial
needs
management
(BEMS)
interrogative
predictive
analytics
maintenance.
integration
AI
presents
transformative
approach
improving
practical
implications
advancement
span
across
design,
construction,
policy
domains,
significant
challenges
need
be
carefully
considered.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery,
Journal Year:
2025,
Volume and Issue:
15(2)
Published: May 1, 2025
ABSTRACT
Rapid
advancements
in
technology
and
Artificial
Intelligence
have
increased
the
volume
of
scientific
research,
making
it
challenging
for
researchers
scholars
to
keep
pace
with
evolving
literature
state‐of‐the‐art
techniques
methods.
Traditional
review
papers
offer
a
way
mitigate
these
difficulties
but
are
often
time‐consuming
labor‐intensive.
This
article
introduces
novel
AI‐assisted
narrative
methodology
that
integrates
advanced
text
retrieval
visualization
techniques,
enhanced
geometric
features,
address
this.
The
proposed
approach
relies
on
automatic
identification
research
topics/clusters
within
large
different
document
corpus
time
periods.
not
only
facilitates
systematic
exploration
trends
over
also
serves
as
valuable
adjunct,
enabling
experts
focus
specific,
homogeneous
areas
fields/clusters.
Initially,
its
generality
mapping
evolution
emerging
topics
described,
revealing
temporal
dynamics
interconnections
series
anomalies.
Subsequently,
method
is
applied
data
an
in‐depth
identified
dominant
cluster
presented.
involves
models
anomaly
detection
analysis.
Focusing
such
subfield
enables
derivation
wealth
characteristics
outcomes
regarding
this
topic,
trends.
process
demonstrates
effectiveness
AI‐driven
reviews
provides
powerful
tool
synthesize
interpret
complex,
dynamically
changing,
fields.
