Hydrological low flow and overlapped trend analysis for drought assessment in Western Black Sea Basin
Natural Hazards,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 22, 2024
Язык: Английский
Performance enhancement of artificial intelligence: A survey
Journal of Network and Computer Applications,
Год журнала:
2024,
Номер
unknown, С. 104034 - 104034
Опубликована: Сен. 1, 2024
Язык: Английский
Combination of Large Language Models and Portable Flood Sensors for Community Flood Response: A Preliminary Study
Water,
Год журнала:
2025,
Номер
17(7), С. 1055 - 1055
Опубликована: Апрель 2, 2025
The
effectiveness
of
early
warning
systems
can
help
people
take
action
to
mitigate
the
impact
extreme
weather
events
once
warnings
are
issued.
developed
by
public
agencies
usually
issue
standard
messages
that,
in
many
situations,
may
not
affect
all
who
receive
messages.
In
long
run,
this
lead
behaviors
respond
relevant
warnings,
resulting
inefficiency.
Users
demand
faster
and
more
customized
information
that
matches
their
needs,
such
as
“How
does
me
right
now?”
or
“What
I
do
impact?”
This
study
proposes
a
decentralized
framework
at
community
level
includes
custom
Internet
Things
(IoT)
sensors
for
timely
monitoring
large
language
models
(LLMs)
generation
user-defined
have
advantages
easy
installation,
low
cost,
affordable
maintenance
fees.
trained
LLMs
expedite
processing
given
specific
prompts
generate
response
users.
addition,
is
established
within
serverless
environment,
enabling
rapid
deployment
scalability.
integration
IoT
demonstrates
how
system
performs
detect
flooding
deliver
real-time,
efficient,
localized
action-ready
different
scenarios.
combination
significantly
enhances
responsiveness
during
flood
events.
Язык: Английский
Disaster Risk Reduction and Management With Emerging Technologies
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 71 - 110
Опубликована: Апрель 17, 2025
This
chapter
explores
the
role
of
emerging
technologies
in
disaster
risk
reduction
and
management
(DRRM),
focusing
on
integration
Internet
Things
(IoT),
Artificial
Intelligence
(AI),
Data
Analytics
to
enhance
urban
resilience.
IoT-enabled
sensors
smart
infrastructure
provide
real-time
data
for
early
warning
systems,
monitoring,
emergency
response.
AI-driven
predictive
analytics
enhances
assessment,
resource
allocation,
post-disaster
recovery,
while
enables
integration,
visualization,
scenario
planning.
Despite
their
potential,
challenges
like
quality,
scalability,
cybersecurity,
ethical
concerns
must
be
addressed.
The
future
Disaster
Risk
Reduction
Management
(DRRM)
will
depend
incorporation
modern
technology,
increased
public
involvement,
global
cooperation,
allowing
cities
develop
more
intelligent,
secure,
sustainable
settings.
Язык: Английский
A Logical Remote Sensing Based Disaster Management and Alert System Using AI-Assisted Internet of Things Technology
K Nagaiah,
Karunakaran Kalaivani,
Radhakrishnan Palamalai
и другие.
Remote Sensing in Earth Systems Sciences,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 24, 2024
Язык: Английский
Navigating Urban Skies: Obstacle Avoidance Strategies for Quadrotor MAVs
Journal of Physics Conference Series,
Год журнала:
2024,
Номер
2866(1), С. 012039 - 012039
Опубликована: Окт. 1, 2024
Abstract
Micro
Aerial
Vehicles
(MAVs)
has
gained
attentions
since
more
than
two
decades
ago
starting
from
the
applications
in
air
combat
up
to
civil
such
as
packet
deliveries,
environmental
monitoring,
and
surveillance.
In
an
environment
cities
that
grows
denser,
navigation
control
for
drones
becomes
challenging
ensure
safe
around
buildings
other
obstacles.
This
study
proposes
approach
obstacle
avoidance
MAVs
by
using
ultrasonic
sensors.
Four
sensors
are
strategically
positioned
cover
front,
right,
back,
left
directions.
Additionally,
a
downward-facing
sensor
measures
quadrotor’s
height
above
ground.
Our
goal
is
develop
autonomous
MAV
can
avoid
obstacles,
ensuring
flight
even
complex
urban
landscapes.
The
scenario
implemented
introducing
any
When
detected
sensor,
signal
will
be
sent
microcontroller
attitude
of
MAVs,
roll
or
pitch
adjusted
moving
counter
direction
obstacle.
We
conducted
20
trials
experiments
varying
gain
values
Proportional
Integral
Derivative
(PID)
values,
we
fine-tune
our
algorithm.
Modifications
include
optimizing
adjustments,
refining
detection
thresholds,
implementing
countermeasures
after
clearance.
results
show
proposed
method
10%
overshoot
when
detecting
obstacles
different
directions
findings
contribute
advancement
efficient
drone
operations,
bridging
gap
between
technology
real-world
challenges.
Язык: Английский
NOWE TECHNOLOGIE W OCHRONIE LUDNOŚCI W POLSCE. ROZWIĄZANIA DOTYCZĄCE PROJEKTU SILVANUS. CZĘŚĆ 2 – TWARDE TECHNOLOGIE I ROZWIĄZANIA SŁUŻĄCE ANGAŻOWANIU SPOŁECZNEMU
Zeszyty Naukowe Pro Publico Bono,
Год журнала:
2024,
Номер
1(1), С. 177 - 192
Опубликована: Дек. 5, 2024
Rozwój
technologiczny
i
związane
z
nim
inżynierskie
sposoby
zapewniania
bezpieczeństwa
determinują
funkcjonowanie
systemu
narodowego
RP
jego
systemów
szczegółowych.
Ich
względna
uniwersalność
sprzyja
implementowaniu
rozwiązań
wypracowanych
w
jednym
kontekście
na
grunt
działań
służących
zapewnianiu
bezpieczeństwaw
innych
kontekstach.
Jest
to
szczególnie
istotne
dla
ochrony
ludności,
której
obecnie
zachodzą
przeobrażenia
konceptualne,
formalne
strukturalne.
Celem
badań
było
określenie
możliwościimplementacji
technicznych
rozwijanych
projekcie
SILVANUS
ludności.
Działania
rzecz
ludności
mogą
być
wspierane
przez
technologie
detekcji,
rozwiązania
obliczeniowe
(w
tym
symulacje
rozwoju
zagrożeń),
tzw.
twarde
(urządzenia),
systemy
wspomagania
decyzji
oraz
służące
angażowaniu
społecznemu.
Część
2
dotyczy
twardych
technologii
(urządzeń)
Można
je
integrować
drodze
optymalizacji
kosztów
bezpieczeństwa.
technologicznysprzyja
kontynuacji
nad
nowymi
technologiami
ochronie