Journal of Advanced Research,
Год журнала:
2023,
Номер
66, С. 31 - 38
Опубликована: Ноя. 24, 2023
The
concept
of
the
metaverse,
a
virtual
world
where
users
can
interact
with
computer-generated
environment,
has
received
significant
attention
recently.
IEEE Internet of Things Journal,
Год журнала:
2023,
Номер
10(21), С. 18469 - 18476
Опубликована: Май 18, 2023
Heart
disease
is
one
of
the
leading
causes
death
worldwide,
and
with
early
detection,
mortality
rates
can
be
reduced.
Well-known
studies
have
shown
that
latest
artificial
intelligence
(AI)
used
to
determine
risk
heart
disease.
However,
existing
did
not
consider
dynamic
scalability
get
best
performance
from
these
AI
models
in
case
an
increasing
number
users.
To
solve
this
problem,
we
proposed
AI-powered
smart
healthcare
framework
called
HealthFaaS,
using
Internet
Things
(IoT)
a
Serverless
Computing
environment
reduce
disease-related
deaths
prevent
financial
losses
by
reducing
misdiagnoses.
HealthFaaS
collects
health
data
users
via
IoT
devices
sends
it
deployed
on
Google
Cloud
Platform
(GCP)-based
serverless
computing
due
its
advantages,
such
as
scalability,
less
operational
complexity,
pay-as-you-go
pricing
model.
The
five
different
for
detection
evaluated
compared
based
key
parameters,
accuracy,
precision,
recall,
$F$
-Score,
AUC.
Experimental
results
demonstrate
light
gradient
boosting
machine
model
gives
highest
success
detecting
diseases
accuracy
rate
91.80%.
Further,
tested
terms
Quality-of-Service
(QoS)
throughput
latency
against
non-serverless
platform.
In
addition,
also
cold
start
platform
which
determined
amount
memory
software
language
makes
direct
impact
latency.
IEEE Internet of Things Journal,
Год журнала:
2023,
Номер
10(20), С. 18016 - 18027
Опубликована: Май 19, 2023
Outdoor
radio
coverage
map
estimation
is
an
important
tool
for
network
planning
and
resource
management
in
modern
Internet
of
Things
(IoT)
cellular
systems.
A
spatially
describes
signal
strength
distribution
provides
information.
practical
problem
to
estimate
fine-resolution
maps
from
sparse
measurements.
However,
nonuniformly
positioned
measurements
access
constraints
pose
challenges
accurate
(RME)
spectrum
many
outdoor
environments.
In
this
work,
we
develop
a
two-phase
learning
framework
RME
by
integrating
well-known
propagation
model
designing
conditional
generative
adversarial
(cGAN).
We
first
explore
global
information
extract
patterns.
Next,
focus
on
the
local
features
shadowing
effect
order
train
optimize
cGAN.
Our
experimental
results
demonstrate
efficacy
proposed
based
models
observations
scenarios.
ACM Computing Surveys,
Год журнала:
2024,
Номер
57(3), С. 1 - 36
Опубликована: Окт. 17, 2024
Recently,
academics
and
the
corporate
sector
have
paid
attention
to
serverless
computing,
which
enables
dynamic
scalability
an
economic
model.
In
users
only
pay
for
time
they
actually
use
resources,
enabling
zero
scaling
optimise
cost
resource
utilisation.
However,
this
approach
also
introduces
cold
start
problem.
Researchers
developed
various
solutions
address
problem,
yet
it
remains
unresolved
research
area.
article,
we
propose
a
systematic
literature
review
on
latency
in
computing.
Furthermore,
create
detailed
taxonomy
of
approaches
latency,
investigate
existing
techniques
reducing
frequency.
We
classified
current
studies
into
several
categories
such
as
caching
application-level
optimisation-based
solutions,
well
Artificial
Intelligence/Machine
Learning-based
solutions.
Moreover,
analyzed
impact
quality
service,
explored
mitigation
methods,
datasets,
implementation
platforms,
them
based
their
common
characteristics
features.
Finally,
outline
open
challenges
highlight
possible
future
directions.
Philosophical Transactions of the Royal Society B Biological Sciences,
Год журнала:
2024,
Номер
379(1904)
Опубликована: Май 5, 2024
Automated
sensors
have
potential
to
standardize
and
expand
the
monitoring
of
insects
across
globe.
As
one
most
scalable
fastest
developing
sensor
technologies,
we
describe
a
framework
for
automated,
image-based
nocturnal
insects—from
development
field
deployment
workflows
data
processing
publishing.
Sensors
comprise
light
attract
insects,
camera
collecting
images
computer
scheduling,
storage
processing.
Metadata
is
important
sampling
schedules
that
balance
capture
relevant
ecological
information
against
power
limitations.
Large
volumes
from
automated
systems
necessitate
effective
We
vision
approaches
detection,
tracking
classification
including
models
built
existing
aggregations
labelled
insect
images.
Data
account
inherent
biases.
advocate
explicitly
correct
bias
in
species
occurrence
or
abundance
estimates
resulting
imperfect
detection
individuals
present
during
occasions.
propose
ten
priorities
towards
step-change
vital
task
face
rapid
biodiversity
loss
global
threats.
This
article
part
theme
issue
‘Towards
toolkit
monitoring’.
Drones,
Год журнала:
2024,
Номер
8(9), С. 483 - 483
Опубликована: Сен. 13, 2024
Fire
accidents
are
life-threatening
catastrophes
leading
to
losses
of
life,
financial
damage,
climate
change,
and
ecological
destruction.
Promptly
efficiently
detecting
extinguishing
fires
is
essential
reduce
the
loss
lives
damage.
This
study
uses
drone,
edge
computing,
artificial
intelligence
(AI)
techniques,
presenting
novel
methods
for
real-time
fire
detection.
proposed
work
utilizes
a
comprehensive
dataset
7187
images
advanced
deep
learning
models,
e.g.,
Detection
Transformer
(DETR),
Detectron2,
You
Only
Look
Once
YOLOv8,
Autodistill-based
knowledge
distillation
techniques
improve
model
performance.
The
approach
has
been
implemented
with
YOLOv8m
(medium)
as
teacher
(base)
model.
distilled
(student)
frameworks
developed
employing
YOLOv8n
(Nano)
DETR
techniques.
attains
best
performance
95.21%
detection
accuracy
0.985
F1
score.
A
powerful
hardware
setup,
including
Raspberry
Pi
5
microcontroller,
camera
module
3,
DJI
F450
custom-built
constructed.
deployed
in
setup
identification.
achieves
89.23%
an
approximate
frame
rate
8
conducted
live
experiments.
Integrating
drone
devices
demonstrates
system’s
effectiveness
potential
practical
applications
hazard
mitigation.
IEEE Access,
Год журнала:
2024,
Номер
12, С. 28684 - 28709
Опубликована: Янв. 1, 2024
In
terms
of
digital
transformation,
organizations
today
are
aware
the
critical
role
that
data
and
information
play
in
their
expansion
development
light
Internet
Things.
To
increase
network
performance
stability,
many
applications
moving
from
cloud
computing
to
edge
(EC).
However,
order
satisfy
customers,
like
intelligent
transportation
systems,
smart
grids,
cities,
healthcare
call
for
even
more
effective
services.
This
survey
addresses
extensive
research
on
two
aspects:
firstly,
we
present
advancements
application
domains
namely
maritime
areas
aerial
systems
integration
with
EC
architecture.
Secondly,
cover
most
recent
technologies,
artificial
intelligence
(AI)
blockchain,
combined
into
paradigm
by
discussing
several
experiments
conducted
various
fields
demonstrate
value
utilizing
them
We
analyze
results
eleven
each
technology
2015
2023.