Eksploatacja i Niezawodnosc - Maintenance and Reliability,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 22, 2024
The
issue
of
risk
assessment
in
road
freight
transport
is
currently
a
significant
research
gap,
which
why
the
authors
decided
to
conduct
this
field.
article
presents
model
for
occurrence
undesirable
events
oversized
cargo.
A
critical
review
literature
on
latest
analysis
and
methods
tools
assessing
presented.
Based
identification
various
events,
proposed
general
approach
using
matrix.
Elements
network
structure
parameterization
cargo
means
were
identified
record
was
provided.
Significant
limitations
indicated
formal
probability
situations
proposed.
An
important
element
presentation
procedure
calculating
effects
practical
example
real
data
Advances in environmental engineering and green technologies book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 333 - 362
Published: Oct. 16, 2024
Explainable
AI
(XAI)
is
important
in
situations
where
decisions
have
significant
effects
on
the
results
to
make
systems
more
reliable,
transparent,
and
people
understand
how
work.
In
this
chapter,
an
overview
of
AI,
its
evolution
are
discussed,
emphasizing
need
for
robust
policy
regulatory
frameworks
responsible
deployment.
Then
key
concept
use
XAI
models
been
discussed.
This
work
highlights
XAI's
significance
sectors
like
healthcare,
finance,
transportation,
retail,
supply
chain
management,
robotics,
manufacturing,
legal
criminal
justice,
etc.
profound
human
societal
impacts.
Then,
with
integrated
IoT
renewable
energy
management
scope
smart
cities
addressed.
The
study
particularly
focuses
implementations
solutions,
specifically
solar
power
integration,
addressing
challenges
ensuring
transparency,
accountability,
fairness
AI-driven
decisions.
Sustainable Futures,
Journal Year:
2024,
Volume and Issue:
8, P. 100278 - 100278
Published: Aug. 12, 2024
Integration
of
advanced
digital
technologies
along
with
ensuring
environmental
sustainability
in
the
logistics
sector
is
becoming
need
hour
novel
multimodal
transportation
concept.
The
rapid
technological
development
era
industry
4.0
can
not
only
create
new
opportunities
achieving
highly
efficient,
intelligent,
and
smart
systems
but
also
enable
business
models
for
value
addition,
additionally,
this
system
will
avoid
degradation
use
scarce
natural
resources
that
contribute
to
climate
change.
This
paper
summarizes
research
trends
these
since
2005
through
a
systematic
literature
review.
results
revealed
mixed
picture
situation,
starting
from
emerging
like
artificial
intelligence,
machine
learning,
blockchain
key
concepts
government
policy
hurdles
lack
impact
breakthroughs
industry.
However,
show
adaptation
improves
overall
environmental,
economic,
social
system.
Vehicles,
Journal Year:
2025,
Volume and Issue:
7(2), P. 38 - 38
Published: April 28, 2025
The
latest
developments
in
Advanced
Driver
Assistance
Systems
(ADAS)
have
greatly
enhanced
the
comfort
and
safety
of
drivers.
These
technologies
can
identify
driver
abnormalities
like
fatigue,
inattention,
impairment,
which
are
essential
for
averting
collisions.
One
important
aspects
this
technology
is
automated
traffic
accident
detection
prediction,
may
help
saving
precious
human
lives.
This
study
aims
to
explore
critical
features
related
prevention.
A
public
US
dataset
was
used
aforementioned
task,
where
various
machine
learning
(ML)
models
were
applied
predict
accidents.
ML
included
Random
Forest,
AdaBoost,
KNN,
SVM.
compared
their
accuracies,
Forest
found
be
best-performing
model,
providing
most
accurate
reliable
classification
accident-related
data.
Owing
black
box
nature
models,
best-fit
model
executed
with
explainable
AI
(XAI)
methods
such
as
LIME
permutation
importance
understand
its
decision-making
given
task.
unique
aspect
introduction
artificial
intelligence
enables
us
human-interpretable
awareness
how
operate.
It
provides
information
about
inner
workings
directs
improvement
feature
engineering
detection,
more
dependable.
analysis
identified
features,
including
sources,
descriptions
weather
conditions,
time
day
(weather
timestamp,
start
time,
end
time),
distance,
crossing,
signals,
significant
predictors
probability
an
occurring.
Future
ADAS
development
anticipated
impacted
by
study’s
conclusions.
adjusted
different
driving
scenarios
identifying
comprehending
dynamics
make
sure
that
systems
precise,
reliable,
suitable
real-world
circumstances.
