Next frontier.,
Год журнала:
2024,
Номер
8(1), С. 185 - 185
Опубликована: Ноя. 27, 2024
The
integration
of
the
Internet
Things
(IoT),
Artificial
Intelligence
(AI),
and
Machine
Learning
(ML)
into
urban
systems
represents
a
transformative
approach
to
addressing
challenges
modern
cities.
By
enabling
real-time
data
collection,
predictive
analytics,
intelligent
decision-making,
these
technologies
enhance
efficiency,
sustainability,
livability
environments.
IoT
sensors
collect
vast
amounts
from
interconnected
systems,
including
transportation,
energy,
waste
management,
public
safety.
AI
ML
algorithms
analyze
this
data,
offering
actionable
insights
optimizing
resource
allocation.
This
research
explores
synergistic
impact
IoT,
AI,
on
emphasizing
applications
such
as
smart
traffic
energy-efficient
buildings,
maintenance
infrastructure.
Additionally,
study
addresses
ethical
technical
implementing
technologies,
privacy,
cybersecurity,
system
scalability.
examining
real-world
case
studies
innovative
frameworks,
paper
highlights
potential
integrated
redefine
planning
paving
way
for
sustainable
cities
future.
Environmental Science and Ecotechnology,
Год журнала:
2024,
Номер
20, С. 100433 - 100433
Опубликована: Май 17, 2024
In
the
dynamic
landscape
of
sustainable
smart
cities,
emerging
computational
technologies
and
models
are
reshaping
data-driven
planning
strategies,
practices,
approaches,
paving
way
for
attaining
environmental
sustainability
goals.
This
transformative
wave
signals
a
fundamental
shift
—
marked
by
synergistic
operation
artificial
intelligence
(AI),
things
(AIoT),
urban
digital
twin
(UDT)
technologies.
While
previous
research
has
largely
explored
AI,
AIoT,
UDT
in
isolation,
significant
knowledge
gap
exists
regarding
their
interplay,
collaborative
integration,
collective
impact
on
context
cities.
To
address
this
gap,
study
conducts
comprehensive
systematic
review
to
uncover
intricate
interactions
among
these
interconnected
technologies,
models,
domains
while
elucidating
nuanced
dynamics
untapped
synergies
complex
ecosystem
Central
four
guiding
questions:
What
theoretical
practical
foundations
underpin
convergence
UDT,
planning,
how
can
components
be
synthesized
into
novel
framework?
How
does
integrating
AI
AIoT
reshape
improve
performance
cities?
augment
capabilities
enhance
processes
challenges
barriers
arise
implementing
what
strategies
devised
surmount
or
mitigate
them?
Methodologically,
involves
rigorous
analysis
synthesis
studies
published
between
January
2019
December
2023,
comprising
an
extensive
body
literature
totaling
185
studies.
The
findings
surpass
mere
interdisciplinary
enrichment,
offering
valuable
insights
potential
advance
development
practices.
By
enhancing
processes,
integrated
offer
innovative
solutions
challenges.
However,
endeavor
is
fraught
with
formidable
complexities
that
require
careful
navigation
mitigation
achieve
desired
outcomes.
serves
as
reference
guide,
spurring
groundbreaking
endeavors,
stimulating
implementations,
informing
strategic
initiatives,
shaping
policy
formulations
sustainable,
development.
These
have
profound
implications
researchers,
practitioners,
policymakers,
providing
roadmap
fostering
resiliently
designed,
technologically
advanced,
environmentally
conscious
environments.
Sustainable Development,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 27, 2024
Abstract
This
study
explores
the
impact
of
artificial
intelligence
(AI)
on
sustainable
development
across
51
countries
during
urbanization.
Using
panel
data,
examines
AI's
effects
through
three
dimensions:
R&D
innovation,
infrastructure,
and
market
advantage.
The
results
demonstrate
that
AI
promotes
development,
with
innovation
exerting
strongest
influence,
followed
by
whereas
advantage
has
smallest
impact.
Additionally,
uncovers
regional
heterogeneity
in
impacts.
In
upper
middle
levels
(60%–70%
quantiles),
promoting
effect
is
strongest.
Moreover,
urbanization
plays
a
threshold
role
relationship
between
development.
When
below
threshold,
infrastructure
promote
inhibit
it.
Conversely,
when
exceeds
this
inhibits
becomes
insignificant,
begin
to
recommends
governments
should
consider
level
crafting
policies
utilizing
AI.
International Journal of Computational and Experimental Science and Engineering,
Год журнала:
2024,
Номер
10(4)
Опубликована: Ноя. 25, 2024
The
rapid
growth
of
big
data
has
created
a
pressing
need
for
advanced
predictive
modeling
techniques
that
can
efficiently
extract
meaningful
insights
from
massive,
complex
datasets.
This
study
explores
deep
computational
intelligence
approaches
to
enhance
in
environments,
focusing
on
the
integration
learning,
swarm
intelligence,
and
hybrid
optimization
techniques.
proposed
framework
employs
Deep
Neural
Network
(DNN)
enhanced
with
Particle
Swarm
Optimization
(PSO)
Adaptive
Gradient
Descent
(AGD)
dynamic
parameter
tuning,
leading
improved
learning
efficiency
accuracy.
is
evaluated
real-world
applications,
including
healthcare
diagnostics,
financial
risk
prediction,
energy
consumption
forecasting.
Experimental
results
demonstrate
significant
improvement
model
performance,
an
accuracy
97.8%
precision
95.2%
mean
absolute
percentage
error
(MAPE)
3.4%
Additionally,
approach
achieves
35%
reduction
overhead
compared
traditional
DNNs
28%
convergence
speed
due
optimization.
work
highlights
potential
integrating
analytics
achieve
robust,
scalable,
efficient
modeling.
Future
research
will
focus
extending
accommodate
real-time
streams
exploring
its
applicability
across
other
domains.
Smart Cities,
Год журнала:
2024,
Номер
7(4), С. 1576 - 1625
Опубликована: Июнь 28, 2024
In
an
era
marked
by
rapid
technological
progress,
the
pivotal
role
of
Artificial
Intelligence
(AI)
is
increasingly
evident
across
various
sectors,
including
local
governments.
These
governmental
bodies
are
progressively
leveraging
AI
technologies
to
enhance
service
delivery
their
communities,
ranging
from
simple
task
automation
more
complex
engineering
endeavours.
As
governments
adopt
AI,
it
imperative
understand
functions,
implications,
and
consequences
these
advanced
technologies.
Despite
growing
importance
this
domain,
a
significant
gap
persists
within
scholarly
discourse.
This
study
aims
bridge
void
exploring
applications
context
government
provision.
Through
inquiry,
seeks
generate
best
practice
lessons
for
smart
city
initiatives.
By
conducting
comprehensive
review
grey
literature,
we
analysed
262
real-world
implementations
170
worldwide.
The
findings
underscore
several
key
points:
(a)
there
has
been
consistent
upward
trajectory
in
adoption
over
last
decade;
(b)
China,
US,
UK
at
forefront
adoption;
(c)
among
technologies,
natural
language
processing
robotic
process
emerge
as
most
prevalent
ones;
(d)
primarily
deploy
28
distinct
services;
(e)
information
management,
back-office
work,
transportation
traffic
management
leading
domains
terms
adoption.
enriches
existing
body
knowledge
providing
overview
current
sphere
governance.
It
offers
valuable
insights
policymakers
decision-makers
considering
adoption,
expansion,
or
refinement
urban
Additionally,
highlights
using
guide
successful
integration
optimisation
future
projects,
ensuring
they
meet
evolving
needs
communities.
Algorithms,
Год журнала:
2025,
Номер
18(1), С. 30 - 30
Опубликована: Янв. 8, 2025
In
the
context
of
booming
construction
smart
cities,
multi-source
data
fusion
and
analysis
algorithms
play
a
key
role
in
optimizing
real
estate
management
improving
urban
efficiency.
this
review,
we
comprehensively
systematically
review
relevant
algorithms,
covering
types,
characteristics,
techniques,
their
synergies
data.
We
found
that
data,
including
sensors,
social
media,
citizen
feedback,
GIS
face
challenges
such
as
quality
privacy
security
when
being
fused.
Data
are
diverse
have
own
advantages
disadvantages.
help
areas
spatial
deep
learning.
Algorithm
collaboration
can
improve
decision-making
accuracy
efficiency
promote
rational
allocation
resources.
future,
algorithm
development
will
focus
on
quality,
real-time,
mining,
interdisciplinary
research,
protection,
collaborative
application
expansion,
providing
strong
support
for
sustainable
cities.
Amidst
the
increasingly
severe
global
environmental
crisis,
application
of
artificial
intelligence
(AI)
in
fields
governance
and
sustainable
development
has
become
a
hot
topic
current
scientific
research
practice.
The
complexity
urgency
issues
have
made
integration
AI
technology
particularly
important
pressing.
To
comprehensively
understand
status,
hotspots,
future
trends
this
field,
study
employed
Citespace
VOSviewer
literature
analysis
tools
to
construct
knowledge
map
based
on
data
from
2004
2024.
results
reveal
that,
terms
regions,
Asia
(especially
China)
most
significant
contributions,
while
North
America
Europe
(particularly
United
States
some
EU
countries)
closely
collaborated,
forming
core
regions.
top
five
authors
publication
volume
are
Liu
J,
Vinuesa
R,
Nishant
Bag
S,
Benzidia
S.
Regarding
themes
field
focus
four
clusters:
intelligent
management
green
innovation
for
performance
lifecycle
assessment,
smart
cities
development,
AI-enabled
management.
These
highlight
vast
potential
enhancing
efficiency
promoting
development.
As
trends,
number
publications
shown
continuous
upward
trend
recent
years,
with
predictions
indicating
that
will
continue
concentrate
keywords
such
as
AI,
life
cycle,
Internet
Things.
In
summary,
is
an
active
expanding
within
governance,
deepen
understanding
topic,
explore
science,
address
challenges,
drive
towards
smart,
efficient,
direction.
