Iraqi Journal of Science,
Год журнала:
2024,
Номер
unknown, С. 1707 - 1724
Опубликована: Март 29, 2024
This
article
suggests
designing
an
intelligent
system
to
rehabilitate
criminals
in
smart
cities,
which
consists
of
two
categories:
the
first
category
a
“smart
social
system,"
managing
behaviors
(good
or
bad)
individuals
as
root
crime
committing.
To
manage
any
criminal
behavior,
we
proposed
electronic
recording
behavior
step,
then
submitting
with
its
under
rehabilitation
theories
second
step
examine
enhancement.
depends
on
prize-and-penalty
principle.
The
penalty
this
is
suspended
sentence
community
services
and
fines
instead
prison
punishment.
constructing
techniques
by
automating
system”
part
police
organization
city.
methodology
working
training
submit
that
should
be
going
standard
cases
process
within
specific
period.
suggested
three
categories
into
prisoner
may
fall;
he
might
fall
"very
bad
people,"
where
needs
go
due
his
worst
actions.
Second,
good
person"
category,
so
punishment
now
over
free
can
released
because
has
enhanced
behavior.
whereas
third
gradual
person
whose
actions
lie
between
these
characteristics;
for
scenario,
our
improve
A
uniform
crossover
genetic
algorithm
been
implemented
check
performance
system.
Thus,
could
very
useful
improving
crime-preventing
systems
population
cities.
Sustainable Cities and Society,
Год журнала:
2023,
Номер
94, С. 104562 - 104562
Опубликована: Март 29, 2023
In
recent
years,
artificial
intelligence
(AI)
has
been
increasingly
put
into
use
to
address
cities'
economic,
social,
environmental,
and
governance
challenges.
Thanks
its
advanced
capabilities,
AI
is
set
become
one
of
local
governments'
principal
means
achieving
smart
sustainable
development.
utilisation
for
urban
planning,
nonetheless,
a
relatively
understudied
area
research,
particularly
in
terms
the
gap
between
theory
practice.
This
study
presents
comprehensive
review
areas
planning
which
technologies
are
contemplated
or
applied,
it
analysed
how
support
could
potentially
Regarding
methodological
approach,
this
systematic
literature
following
PRISMA
protocol.
The
obtained
insights
include:
(a)
Early
adopters'
real-world
applications
paving
way
wider
government
adoption;
(b)
Achieving
adoption
involves
collaboration
partnership
key
stakeholders;
(c)
Big
data
an
integral
element
effective
and;
(d)
Convergence
human
crucial
urbanisation
issues
adequately
achieve
These
highlight
importance
making
smarter
through
analytical
methods.
IEEE Access,
Год журнала:
2023,
Номер
11, С. 60153 - 60170
Опубликована: Янв. 1, 2023
Predicting
crime
using
machine
learning
and
deep
techniques
has
gained
considerable
attention
from
researchers
in
recent
years,
focusing
on
identifying
patterns
trends
occurrences.
This
review
paper
examines
over
150
articles
to
explore
the
various
algorithms
applied
predict
crime.
The
study
provides
access
datasets
used
for
prediction
by
analyzes
prominent
approaches
crime,
offering
insights
into
different
factors
related
criminal
activities.
Additionally,
highlights
potential
gaps
future
directions
that
can
enhance
accuracy
of
prediction.
Finally,
comprehensive
overview
research
discussed
this
serves
as
a
valuable
reference
field.
By
gaining
deeper
understanding
techniques,
law
enforcement
agencies
develop
strategies
prevent
respond
activities
more
effectively.
Deleted Journal,
Год журнала:
2024,
Номер
2024, С. 4 - 16
Опубликована: Март 3, 2024
With
the
escalation
of
cybercriminal
activities,
demand
for
forensic
investigations
into
these
crimeshas
grown
significantly.
However,
concept
systematic
pre-preparation
potential
forensicexaminations
during
software
design
phase,
known
as
readiness,
has
only
recently
gainedattention.
Against
backdrop
surging
urban
crime
rates,
this
study
aims
to
conduct
a
rigorous
andprecise
analysis
and
forecast
rates
in
Los
Angeles,
employing
advanced
Artificial
Intelligence(AI)
technologies.
This
research
amalgamates
diverse
datasets
encompassing
history,
varioussocio-economic
indicators,
geographical
locations
attain
comprehensive
understanding
howcrimes
manifest
within
city.
Leveraging
sophisticated
AI
algorithms,
focuses
on
scrutinizingsubtle
periodic
patterns
uncovering
relationships
among
collected
datasets.
Through
thiscomprehensive
analysis,
endeavors
pinpoint
hotspots,
detect
fluctuations
infrequency,
identify
underlying
causes
criminal
activities.
Furthermore,
evaluates
theefficacy
model
generating
productive
insights
providing
most
accurate
predictionsof
future
trends.
These
predictive
are
poised
revolutionize
strategies
lawenforcement
agencies,
enabling
them
adopt
proactive
targeted
approaches.
Emphasizing
ethicalconsiderations,
ensures
continued
feasibility
use
while
safeguarding
individuals'constitutional
rights,
including
privacy.
The
anticipated
outcomes
tofurnish
actionable
intelligence
law
enforcement,
policymakers,
planners,
aiding
theidentification
effective
prevention
strategies.
By
harnessing
AI,
researchcontributes
promotion
data-driven
models
andprediction,
offering
promising
avenue
enhancing
public
security
Angeles
othermetropolitan
areas.
International Journal of Applied Earth Observation and Geoinformation,
Год журнала:
2022,
Номер
112, С. 102942 - 102942
Опубликована: Авг. 1, 2022
From
an
epidemiological
perspective,
previous
research
on
COVID-19
has
generally
been
based
classical
statistical
analyses.
As
a
result,
spatial
information
is
often
not
used
effectively.
This
paper
uses
image-based
neural
networks
to
explore
the
relationship
between
urban
risk
and
distribution
of
infected
populations,
design
facilities.
To
achieve
this
objective,
we
use
spatio-temporal
data
people
with
new
coronary
pneumonia
prior
28
February
2020
in
Wuhan.
We
then
kriging,
which
method
interpolation,
as
well
core
density
estimation
technology
establish
epidemic
heat
fine
grid
units.
further
evaluate
influence
nine
major
factors,
including
agencies,
hospitals,
park
squares,
sports
fields,
banks
hotels,
by
testing
them
for
significant
positive
correlation
epidemic.
The
weights
these
factors
are
training
Generative
Adversarial
Network
(GAN)
models,
predict
cases
given
area.
input
image
machine
learning
model
city
plan
converted
public
infrastructures,
output
map
results
trained
demonstrate
that
optimising
relevant
point
interests
(POI)
areas
effectively
control
potential
can
aid
managing
preventing
it
from
dispersing
further.
