IEEE Transactions on Artificial Intelligence,
Journal Year:
2024,
Volume and Issue:
5(9), P. 4519 - 4534
Published: April 10, 2024
The
Internet
of
Things
(IoT)
has
been
a
popular
topic
for
research
and
development
in
the
past
decade.
resource-constrained
wireless
nature
IoT
devices
presents
large
surface
vulnerabilities,
traditional
network
security
methods
involving
complex
cryptography
are
not
feasible.
Studies
show
that
Denial
Service
(DoS),
physical
intrusion,
spoofing,
node
forgery
prevalent
threats
IoT,
there
is
need
robust,
lightweight
device
fingerprinting
schemes.
We
identify
eight
criteria
effective
propose
an
intelligent,
lightweight,
whitelist-based
method
satisfies
these
properties.
proposed
uses
power-up
Static
Random
Access
Memory
(SRAM)
stack
as
fingerprint
features
Autoencoder
Networks
(AEN)
registration
verification.
also
present
threat
mitigation
framework
based
on
isolation
levels
to
handle
potential
identified
threats.
Experiments
conducted
with
heterogeneous
pool
ten
AVR
Harvard-architecture
prover
from
different
vendors,
Dell
Latitude
XPS
13
laptops
used
verifier
testbeds.
99.9%
accuracy,
100%
precision,
99.6%
recall
known
unknown
devices,
which
improvement
over
several
works.
independence
fingerprints
stored
AENs
enables
easy
distribution
update,
observed
evaluation
latency
(~
10
−4
seconds)
data
collection
1
second)
make
our
practical
real-world
scenarios.
Lastly,
we
analyze
regard
highlight
its
limitations
future
improvement.
International Journal of Computations Information and Manufacturing (IJCIM),
Journal Year:
2022,
Volume and Issue:
2(2)
Published: Nov. 21, 2022
For
every
sector,
managing
supply
chains
is
a
difficult
task,
but
the
healthcare
sector
faces
risks
and
complication
since
disrupted
chain
could
have
direct
impact
on
patient
security
medical
results.
In
this
assignment
we
will
discuss
how
Blockchain
technology
one
possible
method
for
enhancing
health
E-supply
chain's
security,
integrity,
data
provenance,
usefulness.
The
supply,
product
Internet
of
Medical
Things
(IOMT),
care
are
all
given
such
priority,
goal
research
to
provide
description
advantages
drawbacks
using
blockchain
in
distribution
network.
unfulfilled
potential
increase
requires
greater
research,
analysis,
integration
with
regulatory
frameworks
has
been
discussed.
Energies,
Journal Year:
2022,
Volume and Issue:
15(23), P. 9039 - 9039
Published: Nov. 29, 2022
Green
hydrogen
is
becoming
an
increasingly
important
energy
supply
source
worldwide.
The
great
potential
for
the
use
of
as
a
sustainable
makes
it
attractive
carrier.
In
this
paper,
we
discuss
producing
green
in
Jordan.
Aqaba,
located
south
Jordan,
was
selected
to
study
hydrogen,
due
its
proximity
water
(i.e.,
Red
Sea).
Two
models
were
created
two
electrolyzer
types
using
MATLAB.
investigated
electrolyzers
alkaline
(ALK)
and
polymeric
electrolyte
membrane
(PEM)
electrolyzers.
first
model
used
compare
required
capacity
PV
solar
system
ALK
PEM
from
2022
2025,
depending
on
learning
curves
development
these
technologies.
addition,
predict
total
investment
costs
Then,
techno-economic
constructed
feasibility
technology,
by
comparing
grid
electricity
sources
production
hydrogen.
net
present
value
(NPV)
levelized
cost
(LCOH)
indicators
both
models.
environmental
effect,
according
reduction
CO2
emissions,
also
taken
into
account.
annual
70.956
million
kg.
rate
19.3
kg/s
1783
electrolyzers,
respectively.
LCOH
4.42
USD/kg
3.13
when
applying
generated
system,
payback
period
cover
capital
11
years
project
life,
with
NPV
USD
441.95
million.
Moreover,
emissions
can
be
reduced
3042
tons/year
generation
source,
instead
fossil
fuels
generate
electricity.
savings,
respect
120,135.
Sensors,
Journal Year:
2023,
Volume and Issue:
23(13), P. 6132 - 6132
Published: July 4, 2023
With
the
increasing
growth
rate
of
smart
home
devices
and
their
interconnectivity
via
Internet
Things
(IoT),
security
threats
to
communication
network
have
become
a
concern.
This
paper
proposes
learning
engine
for
that
utilizes
blockchain-based
secure
cloud-based
data
evaluation
layer
segregate
rank
on
basis
three
broad
categories
Transactions
(T),
namely
Smart
T,
Mod
Avoid
T.
The
neural
training
classification
helps
blockchain
with
improvisation
in
decision-making
process.
contributions
this
include
application
user
authentication
generation
ledger
network;
utilization
layer;
enhancement
an
SI-based
algorithm
training;
precise
categories.
proposed
outperformed
Fused
Real-Time
Sequential
Deep
Extreme
Learning
Machine
(RTS-DELM)
system,
fusion
technique,
artificial
intelligence
technology
providing
electronic
information
engineering
analyzing
optimization
schemes
terms
computation
complexity,
false
rate,
qualitative
parameters
lower
average
complexity;
addition,
it
ensures
secure,
efficient
enhance
lifestyle
human
beings.
Sustainability,
Journal Year:
2023,
Volume and Issue:
15(11), P. 8904 - 8904
Published: May 31, 2023
This
paper
aims
to
develop
an
analytical
model
for
the
prediction
of
electricity
produced
in
a
Photovoltaic
Power
Station
(PVS).
In
this
context,
developed
mathematical
is
implemented
Simulink
Model.
The
obtained
simulation
results
are
compared
experimental
data,
from
software
Homer-Pro
model,
and
given
by
online
PV
calculator
(Photovoltaic
Geographical
Information
System),
European
commission.
comparison
show
reliability
specific
months
year.
However,
error
10%
between
simulations
observed
July
August.
mainly
due
effects
humidity
dust
that
were
not
considered
model.
Nevertheless,
monthly
yearly
values
robustness
proposed
predict
PVS
generated
power.
will
be
used
as
powerful
tool
data
optimization
generation.
permits
us
reduce
losses
power
generation
optimizing
connected
generating
stations
grid.
Applied Sciences,
Journal Year:
2025,
Volume and Issue:
15(4), P. 2069 - 2069
Published: Feb. 16, 2025
Data
with
time
attributions
such
as
price,
load,
and
stock,
which
directly
reflect
the
variation
tendency,
are
most
common
type
of
data
character
available.
However,
it
is
difficult
to
predict
complex
volatile
time-series
data.
Further,
density
cluster
methods
employ
existing
train
initial
radius;
however,
a
certain
radius
hard
be
made
suitable
for
continuously
generated
on-going
datasets.
Therefore,
how
select
timespan
according
in
way
that
makes
possible
support
an
adaptive
updated
real-time
calculation
core
process.
In
this
paper,
self-adaptive
multi-density
(SAMD)
prediction
model
proposed
solving
dynamic
selection
problem
so
improve
accuracy
prediction.
This
clustering
method
can
effectively
shorten
iteration
times
achieve
by
jump
sequence,
optimize
points
electricity
price
sequence.
Moreover,
we
especially
focus
on
interval
features
other
multi-source
influencing
factors
together
construct
multi-core
function
double-layer
optimization
calculate
weighted
coefficients,
have
good
adaptability
classification
recognition
performance.
The
experimental
results
show
had
higher
reduced
processing
consumption
order
Advances in civil and industrial engineering book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 139 - 158
Published: Feb. 14, 2025
The
chapter
explores
the
potential
of
AI
in
transforming
SEMS.
AI-based
technologies,
such
as
machine
learning,
neural
networks,
and
IoT
integration,
can
monitor
energy
consumption
real
time,
predict
future
patterns,
modify
or
alter
accordingly
within
residential,
commercial,
industrial
sectors.
In
short,
optimizes
usage
distribution
to
make
it
efficient,
save
money,
environment.
Such
applications
demand
forecasting,
load
balancing,
integration
renewable
systems
highlight
AI's
contribution
toward
sustainability
usage.
Moreover,
sheds
light
on
some
challenges
data
privacy,
system
interoperability,
cost
implementation
with
proposals
innovative
solutions.
On
developments
AI-powered
SEMS,
decentralized
grids,
personalization
management
shall
also
be
addressed.
