Deleted Journal,
Journal Year:
2025,
Volume and Issue:
3(1), P. 165 - 179
Published: Feb. 19, 2025
The
rates
at
which
IoT
is
expanding
are
tremendous,
literally
touching
our
daily
life
experiences
through
various
applications
such
as
smart
city,
healthcare,
agriculture
and
industrial
automation
among-couple
others.
From
amongst
a
number
of
diverse
types
data
produced
by
devices,
image
has
risen
to
the
forefront
one
most
useful
tools
for
real-time
identification
decision
making.
critical
contribution
processing
deep
learning
in
improving
systems
discussed
this
paper.
Image
acquisition,
preprocessing,
segmentation
feature
extraction
procedures
form
basis
acquiring
significant
information
from
raw
imagery
data.
approaches
CNNs,
RNNs,
transfer
learning,
makes
classification
extraction,
object
detection
more
accurate
fully
automated.
These
technologies
have
been
incorporated
used
traffic
monitoring
application,
medical
diagnosis,
environmental
monitoring,
fault
diagnosis
industries.
Nonetheless,
issues
resource
availability,
temporal
delay
security
act
barriers
adoption
microservices
especially
edges
fogs
computing.
To
overcome
these
constraints,
enhancement
on
lightweight
Learning,
Edge
AI
privacy
protection
methodologies
being
advanced
efficient,
secure
real
time
performance.
Hence,
trends
federated
5G
can
also
define
future
based
systems.
This
paper
systematically
critically
reviews
recent
advances
towards
application
architectures
providing
insight
into
its
profile,
challenges
trends.
It
meant
guide
researchers
industry
experts
who
working
building
smarter
scalable
efficient
Cell Reports Physical Science,
Journal Year:
2024,
Volume and Issue:
5(7), P. 102097 - 102097
Published: July 1, 2024
The
rapid
development
of
intelligent
devices
imposes
new
demands
on
electromagnetic
wave
(EMW)-absorbing
materials,
especially
concerning
wide-spectrum
absorption,
frequency
band
manipulation,
and
multifunctional
integration.
However,
conventional
investigations
EMW-absorbing
materials
face
several
challenges
that
collectively
limit
the
effectiveness
existing
amid
growing
demands,
including
ambiguous
(EM)
loss
mechanisms,
impedance
mismatches,
deficiencies
in
integrated
design.
This
review
elucidates
EM
delineates
key
bridge
mechanisms
linking
microscopic
macroscopic
factors,
proposes
dielectric
polarization
models
to
clarify
mechanisms.
Additionally,
it
delves
into
unique
advantages
core-shell
structures
porous
optimization.
Finally,
introduces
fabrication
approaches
integrate
detailing
design
strategies
exploring
potential
applications.
By
consolidating
these
cutting-edge
achievements,
this
aims
guide
scientific
advancement
materials.
Magna Scientia Advanced Research and Reviews,
Journal Year:
2024,
Volume and Issue:
10(1), P. 368 - 378
Published: Feb. 28, 2024
The
exponential
growth
of
network
complexity
and
data
volume
in
modern
digital
ecosystems
has
underscored
the
need
for
innovative
approaches
to
optimize
performance
efficiency.
This
paper
delves
into
potential
AI-driven
optimization
techniques
addressing
this
imperative.
Leveraging
artificial
intelligence
(AI)
algorithms
such
as
machine
learning
deep
learning,
study
investigates
how
AI
can
revolutionize
management
operation
achieve
higher
levels
reliability.
Through
a
comprehensive
review
existing
literature
case
studies,
elucidates
fundamental
principles,
methodologies,
applications
diverse
environments.
It
examines
analyze
vast
amounts
data,
identify
patterns,
make
data-driven
decisions
configurations,
routing
protocols,
resource
allocation
strategies.
Moreover,
explores
enhance
security,
fault
tolerance,
scalability
by
autonomously
detecting
mitigating
threats
vulnerabilities.
Review
succinctly
encapsulates
main
findings
insights
derived
from
analysis,
emphasizing
transformative
efficiency
enhancement.
underscores
benefits
automating
complex
tasks,
reducing
operational
overhead,
adapting
dynamically
changing
conditions
user
demands.
Additionally,
discusses
challenges
considerations
associated
with
implementation
techniques,
including
algorithmic
bias,
privacy
concerns,
ethical
implications.
In
conclusion,
critical
role
evolving
operation.
advocates
continued
research
development
efforts
aimed
at
harnessing
full
unlock
new
infrastructures.
By
embracing
approaches,
organizations
streamline
operations,
improve
experience,
drive
innovation
era.
Energies,
Journal Year:
2024,
Volume and Issue:
17(17), P. 4501 - 4501
Published: Sept. 8, 2024
This
review
paper
thoroughly
explores
the
impact
of
artificial
intelligence
on
planning
and
operation
distributed
energy
systems
in
smart
grids.
With
rapid
advancement
techniques
such
as
machine
learning,
optimization,
cognitive
computing,
new
opportunities
are
emerging
to
enhance
efficiency
reliability
electrical
From
demand
generation
prediction
flow
optimization
load
management,
is
playing
a
pivotal
role
transformation
infrastructure.
delves
deeply
into
latest
advancements
specific
applications
within
context
systems,
including
coordination
resources,
integration
intermittent
renewable
energies,
enhancement
response.
Furthermore,
it
discusses
technical,
economic,
regulatory
challenges
associated
with
implementation
intelligence-based
solutions,
well
ethical
considerations
related
automation
autonomous
decision-making
sector.
comprehensive
analysis
provides
detailed
insight
how
reshaping
grids
highlights
future
research
development
areas
that
crucial
for
achieving
more
efficient,
sustainable,
resilient
system.
Angewandte Chemie International Edition,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Aug. 14, 2024
The
solar-driven
photorechargeable
zinc-ion
batteries
have
emerged
as
a
promising
power
solution
for
smart
electronic
devices
and
equipment.
However,
the
subpar
cyclic
stability
of
Zn
anode
remains
significant
impediment
to
their
practical
application.
Herein,
poly(diethynylbenzene-1,3,5-triimine-2,4,6-trione)
(PDPTT)
was
designed
functional
polymer
coating
Zn.
Theoretical
calculations
demonstrate
that
PDPTT
not
only
significantly
homogenizes
electric
field
distribution
on
surface,
but
also
promotes
ion-accessible
surface
With
multiple
N
C=O
groups
exhibiting
strong
adsorption
energies,
this
reduces
nucleation
overpotential
Zn,
alters
diffusion
pathway
ACM Computing Surveys,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 16, 2025
The
increasing
utilization
of
surveillance
cameras
in
smart
cities,
coupled
with
the
surge
online
video
applications,
has
heightened
concerns
regarding
public
security
and
privacy
protection,
which
propelled
automated
Video
Anomaly
Detection
(VAD)
into
a
fundamental
research
task
within
Artificial
Intelligence
(AI)
community.
With
advancements
deep
learning
edge
computing,
VAD
made
significant
progress
advances
synergized
emerging
applications
cities
internet,
moved
beyond
conventional
scope
algorithm
engineering
to
deployable
Networking
Systems
for
(NSVAD),
practical
hotspot
intersection
exploration
AI,
IoVT,
computing
fields.
In
this
article,
we
delineate
foundational
assumptions,
frameworks,
applicable
scenarios
various
learning-driven
routes,
offering
an
exhaustive
tutorial
novices
NSVAD.
addition,
article
elucidates
core
concepts
by
reviewing
recent
typical
solutions
aggregating
available
resources
accessible
at
https://github.com/fdjingliu/NSVAD.
Lastly,
projects
future
development
trends
discusses
how
integration
AI
technologies
can
address
existing
challenges
promote
open
opportunities,
serving
as
insightful
guide
prospective
researchers
engineers.
