Telesurgery: current status and strategies for latency reduction
Journal of Robotic Surgery,
Год журнала:
2025,
Номер
19(1)
Опубликована: Апрель 12, 2025
Язык: Английский
From Sensors to Data Intelligence: Leveraging IoT, Cloud, and Edge Computing with AI
Sensors,
Год журнала:
2025,
Номер
25(6), С. 1763 - 1763
Опубликована: Март 12, 2025
The
exponential
growth
of
connected
devices
and
sensor
networks
has
revolutionized
data
collection
monitoring
across
industries,
from
healthcare
to
smart
cities.
However,
the
true
value
these
systems
lies
not
merely
in
gathering
but
transforming
it
into
actionable
intelligence.
integration
IoT,
cloud
computing,
edge
AI
offers
a
robust
pathway
achieve
this
transformation,
enabling
real-time
decision-making
predictive
insights.
This
paper
explores
innovative
approaches
combine
technologies,
emphasizing
their
role
decision-making,
analytics,
low-latency
processing.
work
analyzes
several
among
cloud/edge
through
examples
applications,
highlighting
challenges
seamlessly
integrate
techniques
pervasive
environmental
findings
contribute
advancing
intelligence,
offering
roadmap
for
building
smarter,
more
sustainable
infrastructure.
Язык: Английский
A holistic platform for adverse drug reaction prevention and monitoring: leveraging service-oriented architecture for tailored healthcare solutions
Service Oriented Computing and Applications,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 11, 2025
Язык: Английский
A Scalable Hybrid Edge-Cloud Approach to Minimizing Latency in IoT Applications
International Journal of Computational and Experimental Science and Engineering,
Год журнала:
2025,
Номер
11(2)
Опубликована: Апрель 13, 2025
The
increasing
reliance
on
IoT
applications
demands
efficient,
scalable
solutions
to
address
latency,
a
critical
factor
in
time-sensitive
operations.
Hybrid
Edge-Cloud
approaches
leverage
the
strengths
of
both
edge
and
cloud
computing
optimize
performance
ensure
seamless
connectivity.
However,
existing
methods
often
struggle
with
excessive
latency
due
resource
allocation
inefficiencies,
limited
device
capabilities,
network
congestion.
This
study
proposes
model
based
Scalable
Approach
(SHECA)
framework,
designed
mitigate
these
challenges
applications.
SHECA
integrates
for
real-time
data
processing
storage,
advanced
analytics,
long-term
decision-making.
By
dynamically
distributing
computational
loads
leveraging
intelligent
allocation,
framework
significantly
reduces
enhances
system
responsiveness.
findings
demonstrate
that
average
by
35%
compared
traditional
cloud-only
methods,
ensuring
faster
response
times,
scalability,
improved
user
experience
hybrid
solution
offers
robust
approach
minimization
diverse
scenarios.
Язык: Английский
A comparative study of neural network pruning strategies for industrial applications
Frontiers in Computer Science,
Год журнала:
2025,
Номер
7
Опубликована: Апрель 17, 2025
Introduction
In
recent
years,
Deep
Learning
(DL)
and
Artificial
Neural
Networks
(ANNs)
have
transformed
industrial
applications
by
providing
automation
in
complex
tasks
such
as
anomaly
detection
predictive
maintenance.
However,
traditional
DL
models
often
need
significant
computational
resources,
making
them
unsuitable
for
resource-constrained
edge
devices.
This
paper
explores
the
potential
of
sparse
ANNs
to
address
these
challenges,
focusing
on
their
application
settings.
Methods
We
perform
an
experimental
comparison
pruning
techniques,
including
Pre-Training,
In-Training,
Post-Training,
SET
method,
applied
VGG16
ResNet18
architectures,
conduct
a
systematic
analysis
methodologies
alongside
effects
varying
sparsity
levels,
analyze
efficiency
object
classification
tasks.
Key
metrics
training
accuracy,
inference
time,
energy
consumption
are
analyzed
assess
feasibility
deploying
Results
discussion
Our
results
demonstrate
that
ANNs,
particularly
when
pruned
using
achieve
savings
without
compromising
suitable
applications.
work
highlights
neural
networks
boost
sustainability
environments,
paving
way
large
adoption
computing
scenarios.
Язык: Английский
Valorization of Food Waste Stream by Harnessing Bioactive Compounds: A Comprehensive Review on the Process, Challenges and Solutions
Food Bioscience,
Год журнала:
2025,
Номер
unknown, С. 106833 - 106833
Опубликована: Май 1, 2025
Язык: Английский
An Integrated MCDM Framework for Trust-aware and Fair Task Offloading in Heterogeneous Multi-Provider Edge-Fog-Cloud Systems
Results in Engineering,
Год журнала:
2025,
Номер
unknown, С. 105228 - 105228
Опубликована: Май 1, 2025
Язык: Английский
Internet of Things-Based Anomaly Detection Hybrid Framework Simulation Integration of Deep Learning and Blockchain
Information,
Год журнала:
2025,
Номер
16(5), С. 406 - 406
Опубликована: Май 15, 2025
IoT
environments
have
introduced
diverse
logistic
support
services
into
our
lives
and
communities,
in
areas
such
as
education,
medicine,
transportation,
agriculture.
However,
with
new
technologies
services,
the
issue
of
privacy
data
security
has
become
more
urgent.
Moreover,
rapid
changes
capabilities
attacks
highlighted
need
for
an
adaptive
reliable
framework.
In
this
study,
we
applied
proposed
simulation
to
hybrid
framework,
making
use
deep
learning
continue
monitoring
data;
also
used
blockchain
association
framework
log,
tackle,
manage,
document
all
sensor’s
points.
Five
sensors
were
run
a
SimPy
environment
check
examine
framework’s
capability
real-time
environment;
(ANN)
technique
integrated
enhance
efficiency
detecting
certain
(benign,
part
horizontal
port
scan,
attack,
C&C,
Okiru,
DDoS,
file
download)
logging
sensor
data,
respectively.
The
comparison
different
machine
(ML)
models
showed
that
DL
outperformed
them.
Interestingly,
evaluation
results
mature
moderate
level
accuracy
precision
reached
97%.
confirmed
superior
performance
under
varied
conditions
like
attack
types
network
sizes
comparing
other
approaches.
It
can
improve
its
over
time
detect
anomalies
environments.
Язык: Английский
Internet of Vehicles for Sustainable Smart Cities
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 35 - 68
Опубликована: Май 28, 2025
The
Internet
of
Vehicles
(IoV)
is
revolutionizing
urban
mobility
by
enabling
intelligent
transportation
systems,
enhancing
road
safety,
optimizing
traffic
flow,
and
reducing
environmental
impacts.
This
chapter
explores
the
role
IoV
in
development
sustainable
smart
cities,
focusing
on
its
integration
with
key
technologies
such
as
5G,
AI,
IoT,
edge
computing.
It
provides
insights
into
IoV's
contributions
to
green
mobility,
management,
energy
efficiency,
alongside
discussing
challenges,
security
concerns,
policy
implications
that
must
be
addressed
for
widespread
implementation.
concludes
highlighting
emerging
trends
future
research
directions.
Язык: Английский