Buildings,
Journal Year:
2024,
Volume and Issue:
14(11), P. 3349 - 3349
Published: Oct. 23, 2024
This
paper
presents
an
IoT-based
solution
for
detecting
grouting
voids
in
tunnel
construction
using
the
Raspberry
Pi
microcomputer.
Voids
between
primary
and
secondary
linings
can
compromise
structural
integrity,
traditional
methods
like
GPR
lack
continuous
feedback.
The
proposed
system
uses
embedded
electrical
wires
lining
to
measure
conductivity,
with
disruptions
indicating
unfilled
voids.
monitors
this
real
time,
uploading
data
a
cloud
platform
engineer
access
via
smartphone.
Field
tests
were
conducted
full-scale,
600
m
long
evaluate
system’s
effectiveness.
demonstrated
accuracy
various
geometries,
including
straight
sections,
curves,
intersections.
Using
only
void
detection
system,
largest
detected
post-grouting
was
1.8
cm,
which
is
within
acceptable
limits
does
not
tunnel’s
integrity
or
safety.
proved
be
cost-effective
scalable
real-time
monitoring
during
process,
eliminating
need
manual
inspections.
study
highlights
potential
of
solutions
smart
construction,
providing
reliable
practical
method
improving
safety
operational
efficiency
operations.
Deleted Journal,
Journal Year:
2024,
Volume and Issue:
4(2), P. 639 - 647
Published: March 26, 2024
The
construction
industry
faces
challenges
such
as
project
complexity,
delays,
and
communication
issues.
Leveraging
AI,
particularly
through
data
analysis,
predictive
analytics,
machine
learning,
addresses
these
by
optimizing
planning,
scheduling,
risk
management.
This
paper
outlines
strategies
for
AI
integration,
including
collection,
learning
algorithms,
cloud
computing.
Case
studies
highlight
successful
implementations,
showcasing
benefits
increased
efficiency,
cost
savings,
improved
safety.
However,
like
security
workforce
acceptance
must
be
considered.
abstract
concludes
discussing
future
trends
encouraging
the
to
embrace
enhanced
outcomes.
International Journal of Computational and Experimental Science and Engineering,
Journal Year:
2024,
Volume and Issue:
10(3)
Published: Aug. 6, 2024
The
prediction
of
malicious
nodes
in
Internet
Things
(IoT)
networks
is
crucial
for
enhancing
network
security.
Malicious
can
significantly
impact
performance
across
various
scenarios.
Machine
learning
(ML)
classification
algorithms
provide
binary
outcomes
("yes"
or
"no")
to
accurately
identify
these
nodes.
This
study
implements
classifier
address
the
problem
node
classification,
using
“SensorNetGuard”
dataset.
dataset,
comprising
10,000
records
with
21
features,
was
preprocessed
and
used
train
multiple
ML
models,
including
Logistic
Regression,
Decision
Tree,
Naive
Bayes,
K-Nearest
Neighbors
(KNN),
Support
Vector
(SVM).
Performance
evaluation
models
followed
workflow,
utilizing
Python
libraries
such
as
scikit-learn,
Seaborn,
Matplotlib,
Pandas.
results
indicated
that
Bayes
outperformed
others
an
accuracy
98.1%.
paper
demonstrates
effectiveness
classifiers
detecting
IoT
networks,
providing
a
robust
predictive
model
real-time
application.
dataset
available
on
IEEE
data
port
Kaggle
platform.
Sustainability,
Journal Year:
2025,
Volume and Issue:
17(2), P. 585 - 585
Published: Jan. 14, 2025
As
material
scarcity
and
environmental
concerns
grow,
reuse
waste
reduction
are
gaining
attention
based
on
their
potential
to
reduce
carbon
emissions
promote
net-zero
buildings.
This
study
develops
an
innovative
approach
that
combines
multi-modal
sensing
technologies
with
machine
learning
enable
contactless
assessment
of
in
situ
building
materials
for
potential.
By
integrating
thermal
imaging,
red,
green,
blue
(RGB)
cameras,
as
well
depth
sensors,
the
system
analyzes
conditions
reveals
hidden
geometries
within
existing
enhances
understanding
by
analyzing
materials,
including
compositions,
histories,
assemblies.
A
case
drywall
deconstruction
demonstrates
these
can
effectively
guide
process,
potentially
reducing
costs
significantly.
The
findings
highlight
feasible
scenarios
offer
insights
into
improving
techniques
through
automated
feedback
visualization
cut
lines
fastener
positions.
research
indicates
methods
technically
viable,
economically
advantageous,
environmentally
beneficial.
Serving
initial
step
toward
novel
view
classify
this
lays
a
foundation
future
research,
promoting
sustainable
construction
practices
optimize
negative
impact.
International Journal of Applied Research in Social Sciences,
Journal Year:
2024,
Volume and Issue:
6(3), P. 173 - 184
Published: March 8, 2024
In
the
face
of
rapidly
changing
climate
conditions,
field
HVAC
(Heating,
Ventilation,
and
Air
Conditioning)
system
design
project
management
is
confronted
with
a
myriad
challenges.
This
review
delves
into
critical
importance
assessing
impact
change
on
these
aspects
highlights
key
considerations
for
industry
professionals.
Climate
poses
multifaceted
challenges
to
management,
primarily
due
its
influence
temperature
patterns,
extreme
weather
events,
evolving
energy
demands.
Rising
global
temperatures
necessitate
innovative
approaches
cooling
systems,
focus
efficiency
sustainable
practices.
Furthermore,
increasing
frequency
intensity
heatwaves
cold
spells
demand
systems
that
can
adapt
dynamically
fluctuating
environmental
conditions.
The
underscores
significance
incorporating
projections
future-proofing
strategies
design.
By
leveraging
predictive
modeling
techniques
data,
engineers
optimize
performance,
minimize
consumption,
enhance
indoor
air
quality
amidst
climatic
Additionally,
integration
renewable
sources
such
as
solar
geothermal
technologies
explored
means
mitigate
reduce
reliance
fossil
fuels.
Effective
in
context
entails
proactive
risk
assessment
mitigation
strategies.
Project
managers
must
anticipate
potential
disruptions
arising
from
supply
chain
disruptions,
regulatory
changes
influenced
by
policies.
Adopting
adaptive
methodologies
enables
stakeholders
respond
swiftly
emerging
ensure
resilience
uncertainties.
imperative
embrace
approach
towards
management.
prioritizing
resilience,
sustainability,
innovation,
professionals
navigate
complexities
posed
contribute
more
resilient
built
environment.
Keywords:
Change,
HVAC,
Management,
System
Design,
Review.
SSRN Electronic Journal,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 1, 2024
This
research
paper
explores
the
transformative
possibilities
arising
from
integration
of
ChatGPT,
an
advanced
language
model,
into
domain
intelligent
manufacturing.
In
face
rapid
changes
in
manufacturing
landscape,
there
is
increasing
demand
for
adaptive
and
systems
to
elevate
efficiency,
productivity,
decision-making
processes.
study
investigates
incorporation
ChatGPT's
or
Bard
cutting-edge
natural
processing
capabilities
various
forefront
aspects
establish
a
novel
paradigm
The
ChatGPT
processes
presents
versatile
approach
tackle
challenges
seize
opportunities
within
modern
production
systems.
A
pivotal
aspect
this
lies
augmenting
human-machine
collaboration
factory.
understanding
facilitates
seamless
communication
between
human
operators
automated
systems,
fostering
more
intuitive
responsive
environment.
Additionally,
delves
utilization
predictive
maintenance
facilities.
Through
analysis
historical
data
real-time
information,
can
provide
insights
potential
equipment
failures,
enabling
proactive
strategies
that
mitigate
downtime
optimize
resource
utilization.
also
application
supply
chain
management.
model's
capacity
process
vast
amounts
textual
contributes
improved
forecasting,
inventory
optimization,
risk
results
resilient
agile
ecosystem
capable
adapting
dynamic
market
conditions.
Furthermore,
role
quality
control
defect
detection.
model
analyze
intricate
patterns
data,
identifying
anomalies
defects
with
high
degree
accuracy.
Integrating
assurance
ensures
higher
product
quality,
reducing
waste,
enhancing
overall
customer
satisfaction.
findings
highlight
revolutionize
processes,
propelling
industry
towards
greater
adaptability,
competitiveness
rapidly
evolving
global
market.
Buildings,
Journal Year:
2024,
Volume and Issue:
14(7), P. 2137 - 2137
Published: July 11, 2024
Buildings
significantly
contribute
to
global
energy
consumption
and
greenhouse
gas
emissions.
This
systematic
literature
review
explores
the
potential
of
artificial
intelegence
(AI)
enhance
sustainability
throughout
a
building’s
lifecycle.
The
identifies
AI
technologies
applicable
sustainable
building
practices,
examines
their
influence,
analyses
implementation
challenges.
findings
reveal
AI’s
capabilities
in
optimising
efficiency,
enabling
predictive
maintenance,
aiding
design
simulation.
Advanced
machine
learning
algorithms
facilitate
data-driven
analysis,
while
digital
twins
provide
real-time
insights
for
decision-making.
also
barriers
adoption,
including
cost
concerns,
data
security
risks,
While
offers
innovative
solutions
optimisation
environmentally
conscious
addressing
technical
practical
challenges
is
crucial
its
successful
integration
practices.
SSRN Electronic Journal,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 1, 2024
The
urgent
acceleration
of
climate
change
necessitates
the
development
innovative
and
adaptive
mitigation
strategies.
This
study
investigates
how
ChatGPT
or
Bard,
an
advanced
language
model,
enhances
efforts
to
mitigate
change.
By
leveraging
natural
processing
machine
learning,
facilitates
improved
communication,
collaboration,
decision-making
among
stakeholders,
thereby
accelerating
implementation
paper
begins
by
examining
context
change,
emphasizing
need
for
robust
measures.
It
underscores
limitations
traditional
approaches
introduces
transformative
potential
integrating
into
action
frameworks.
model's
capacity
analyze
extensive
datasets
generate
human-like
text
allows
it
comprehend
intricate
science,
distill
key
insights,
communicate
them
effectively.
research
identifies
strategies
that
benefit
from
ChatGPT's
intervention.
One
such
strategy
involves
optimizing
deployment
renewable
energy.
assists
in
identifying
optimal
locations
energy
infrastructure,
considering
geographical
climatic
factors.
Additionally,
model
aids
developing
sophisticated
management
systems,
enhancing
efficiency
reliability
sources.
In
sustainable
agriculture,
contributes
providing
real-time
data
analysis
precision
farming.
helps
farmers
optimize
resource
utilization,
minimize
environmental
impact,
adopt
climate-resilient
agricultural
practices.
Moreover,
formulating
policies
promote
land
use
forest
conservation.
also
explores
role
resilience
through
risk
assessment
adaptation
planning.
analyzing
data,
vulnerable
regions
targeted
infrastructure
resilience,
disaster
preparedness,
community
engagement.
Furthermore,
discusses
fostering
global
collaboration.
cross-border
information
exchange,
knowledge
sharing,
formulation
unified
policies.
collaborative
approach
is
essential
addressing
transboundary
nature
achieving
international
goals.
harnessing
capabilities,
stakeholders
can
unlock
new
dimensions
innovation,
paving
way
a
more
resilient
future.
SSRN Electronic Journal,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 1, 2024
This
research
delves
into
the
utilization
of
advanced
artificial
intelligence
(AI),
specifically
ChatGPT
or
Bard,
to
improve
strategies
for
monitoring
and
controlling
water
air
pollution.
Given
escalating
concerns
surrounding
environmental
degradation
its
repercussions
on
public
health,
there
is
a
pressing
demand
innovative
pollution
management
techniques.
investigation
centers
harnessing
capabilities
ChatGPT,
an
language
model,
address
real-time
data
analysis,
decision-making,
engagement
challenges
within
realm
quality.
Incorporating
cutting-edge
methods
in
monitoring,
such
as
sensor
networks,
satellite
imagery,
IoT
devices,
this
aims
obtain
comprehensive
understanding
dynamics.
Nevertheless,
substantial
volume
presents
processing
extracting
meaningful
insights.
employed
intelligent
tool
proficient
comprehending
natural
queries
delivering
insightful
analyses.
integration
streamlines
interpretation
intricate
sets,
enabling
swift
decision-making
control
authorities.
Moreover,
assumes
pivotal
role
by
serving
user-friendly
interface
disseminating
information
levels,
regulatory
measures,
preventive
actions.
Through
interactive
conversations,
it
enhances
communication
between
agencies
general
public,
cultivating
awareness
encouraging
participation
initiatives.
paper
underscores
significance
collaborative
human-AI
approach
tackling
multifaceted
The
also
ethical
considerations
associated
with
AI-driven
emphasizing
importance
responsible
AI
implementation.
As
technologies
progress,
proposed
framework
contribute
ongoing
discourse
sustainable
involvement.
By
synergizing
state-of-the-art
techniques,
seeks
offer
efficacious
solution
advancing
contemporary
landscape.
SSRN Electronic Journal,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 1, 2024
The
infusion
of
generative
artificial
intelligence
(AI)
stands
out
as
a
transformative
influence
in
civil
engineering,
reshaping
conventional
methodologies
and
elevating
the
effectiveness
precision
across
various
domains.
This
study
delves
into
nuanced
impact
ChatGPT,
potent
language
model,
key
realms
within
engineering:
Structural
Engineering,
Geotechnical
Transportation
Environmental
Water
Resources
Urban
Regional
Planning,
Materials
Coastal
Earthquake
Engineering.
Within
ChatGPT
assumes
central
role
formulating
refining
structural
designs.
By
deciphering
intricate
engineering
concepts
proposing
inventive
solutions,
assists
engineers
crafting
structures
that
not
only
exhibit
resilience
but
also
optimize
resource
utilization.
Its
proficiency
scrutinizing
extensive
datasets
delivering
insights
positions
it
an
invaluable
tool
for
augmenting
integrity
safety.
Engineering
benefits
from
ChatGPT's
aptitude
processing
interpreting
geological
geophysical
data.
Through
generation
reports
analyses,
aids
recognizing
potential
risks
suggesting
mitigation
strategies,
thereby
expediting
decision-making
geotechnical
projects.
In
realm
application
involves
streamlining
traffic
flow,
devising
intelligent
transportation
systems,
overall
infrastructure
planning.
natural
capabilities
facilitate
seamless
communication
collaboration
among
diverse
stakeholders
engaged
contributes
to
evaluation
environmental
studies,
assisting
planners
making
well-informed
decisions
prioritizing
sustainability.
Moreover,
its
capability
simulate
scenarios
formulation
effective
pollution
control
measures.
leverages
data
interpretation
modeling,
enabling
precise
predictions
water
flow
patterns
aiding
design
efficient
management
systems.
extends
contributions
where
urban
development
optimizing
land
use,
addressing
challenges
associated
with
population
growth
urbanization.
prowess
analysis
materials
enhanced
properties,
resilient
coastal
structures,
creation
earthquake-resistant
infrastructure.
research
paper
scrutinizes
how
integration
these
disciplines
heightens
efficiency
practices
unlocks
new
avenues
innovation,
sustainability,
face
evolving
challenges.
Journal of Information Technology in Construction,
Journal Year:
2025,
Volume and Issue:
30, P. 65 - 91
Published: Feb. 23, 2025
The
construction
industry's
shift
to
data-driven
project
management
has
led
the
increasing
adoption
of
various
sensing
technologies.
transition
triggers
a
demand
for
workforce
skilled
in
both
technical
and
analytical
aspects
these
tools.
While
technologies
data
analytics
can
support
processes,
inherent
complexity
sensor
processing
often
exceeds
skill
sets
graduating
workforce.
Further,
integrating
sensor-based
applications
into
curricula
lacks
evidence
effectiveness
training
future
professionals.
Computational
thinking-supported
practices
allow
students
perform
analytics,
spanning
from
generation
visualization.
This
pilot
study
utilizes
InerSens,
block
programming
interface,
as
pedagogical
tool
develop
students’
computational
thinking
through
ergonomic
risk
assessment.
Twenty-six
undergraduate
were
engaged
instructional
units
using
wearable
sensors,
data,
InerSens.
approach
was
evaluated
by
examining
students'
perceived
self-efficacy
skills,
task
performance
reflections,
technology
acceptance.
Results
show
gains
self-efficacy,
positive
acceptance,
satisfactory
on
course
assignments.
contributes
Learning-for-Use,
constructivism,
constructionism
frameworks
graphical
interactive
objects
procedural
knowledge
summatively
assessing
how
learn
address
challenges
with
analytics.