Ingénierie des systèmes d information,
Journal Year:
2024,
Volume and Issue:
29(3), P. 1183 - 1193
Published: June 20, 2024
Flooding
is
a
natural
disaster
that
has
serious
impact
on
humans,
the
environment,
and
economy.To
reduce
risk
adverse
impacts
of
flooding,
this
research
aims
to
design
an
Internet
Things
(IoT)
based
early
detection
system
integrated
with
decision
support
system.The
proposed
uses
various
types
sensors,
such
as
DHT22
monitor
air
temperature
humidity,
Ombrometer
measure
rainfall,
Water
Flow
Sensor
water
flow,
Ultrasonic
detect
changes
in
level.Data
from
these
sensors
will
be
collected
real
time
analyzed
predict
potential
flooding.In
addition,
have
user
interface
facilitates
monitoring
decisionmaking
by
authorities.The
use
sensor
data
weather
information
warn
decision-makers
flooding
appropriate
action
recommendations.This
expected
improve
ability
respond
floods
more
effectively,
thereby
assisting
protecting
human
lives,
reducing
economic
floods.In
contributes
development
IoT-based
technologies
systems
context
mitigation.
Water Conservation and Management,
Journal Year:
2023,
Volume and Issue:
7(2), P. 97 - 106
Published: June 20, 2023
Water
is
an
important
element
for
all
living
things.
It
very
to
have
sustainability
in
drinking
water
operations.
This
because
operations
means
continuous
supply
without
interruption.
Sustainability
related
risk
management.
can
be
said
that
a
good
index
must
assessed
using
However
existing
has
proved
inaccuracy,
this
seen
from
the
parameter
same
weight
between
each
other.
An
additional
method
such
as
Artificial
intelligence
and
IoT
was
needed
enhance
accuracy
of
index.
(artificial
IoT)
used
enhancement
management
parameters
based
on
its
severity,
thus
impacting
accuracy.
In
paper,
we
propose
review
detailed
research
sustainable
supplies.
Various
challenges
(issues)
exist
are
inside
presented
together
with
future
direction
artificial
framework.
A
operation
combined
enhanced
(IoT
intelligence)
boost
(assessment)
Advances in environmental engineering and green technologies book series,
Journal Year:
2023,
Volume and Issue:
unknown, P. 31 - 45
Published: June 9, 2023
This
chapter
introduces
an
innovative
solution
to
address
sewage
pollution
by
integrating
AI-enabled
waste
management
systems.
The
approach
involves
segregating
into
solid
and
liquid
streams
applying
specialized
treatment
processes.
main
goal
is
achieve
sustainable
treatment,
recover
valuable
resources,
produce
distilled
water.
To
ensure
optimal
performance,
AI
system
leveraging
cutting-edge
technologies
like
IoT,
machine
learning,
computer
vision
employed
for
real-time
monitoring,
water
quality
assessment,
problem
resolution.
These
findings
contribute
significantly
the
advancement
of
practices.
They
effectively
reduce
soil
pollution,
safeguard
groundwater
levels,
enhance
overall
operational
efficiency.
technology-driven
strategy
paves
path
a
more
eco-friendly
advanced
future
in
management.
Journal of Advanced Research in Applied Sciences and Engineering Technology,
Journal Year:
2023,
Volume and Issue:
36(1), P. 217 - 240
Published: Dec. 24, 2023
Saudi
Arabia's
agriculture
heavily
depends
on
effective
water
management,
given
its
limited
freshwater
resources
and
arid
climate.
Real-time
monitoring
of
soil
moisture
levels,
weather
conditions,
crop
watering
needs,
facilitated
by
IoT
integration,
plays
a
crucial
role
in
conserving
minimizing
waste.
The
resultant
improvements
yields
quality
are
essential
for
the
long-term
success
country.
This
study
employs
Technique
Order
Preference
Similarity
to
Ideal
Solution
(TOPSIS)
method
investigate
transformative
potential
Internet
Things
(IoT)
enhancing
management
practices
sector.
research
begins
highlighting
significance
agriculture,
emphasizing
proportion
land
Arabia
allocated
agricultural
purposes.
problem
statement
underscores
pressing
challenges
encompassing
issues
such
as
scarcity,
inefficient
irrigation
methods,
need
real-time
data
inform
decision-making.
To
address
these
challenges,
proposes
an
IoT-based
Agricultural
Water
Management
System
(IoT-AWMS)
that
leverages
sensors,
analytics,
machine
learning
algorithms.
system
is
designed
optimize
utilization
agriculture.
Simulations
conducted
within
demonstrate
significant
enhancement
usage
efficiency,
resulting
reduced
wastage
increased
yields.
In
conclusion,
this
critical
importance
proposed
Arabia.
It
positioned
valuable
tool
mitigating
scarcity
promoting
environmentally
sustainable
Ingénierie des systèmes d information,
Journal Year:
2024,
Volume and Issue:
29(3), P. 1183 - 1193
Published: June 20, 2024
Flooding
is
a
natural
disaster
that
has
serious
impact
on
humans,
the
environment,
and
economy.To
reduce
risk
adverse
impacts
of
flooding,
this
research
aims
to
design
an
Internet
Things
(IoT)
based
early
detection
system
integrated
with
decision
support
system.The
proposed
uses
various
types
sensors,
such
as
DHT22
monitor
air
temperature
humidity,
Ombrometer
measure
rainfall,
Water
Flow
Sensor
water
flow,
Ultrasonic
detect
changes
in
level.Data
from
these
sensors
will
be
collected
real
time
analyzed
predict
potential
flooding.In
addition,
have
user
interface
facilitates
monitoring
decisionmaking
by
authorities.The
use
sensor
data
weather
information
warn
decision-makers
flooding
appropriate
action
recommendations.This
expected
improve
ability
respond
floods
more
effectively,
thereby
assisting
protecting
human
lives,
reducing
economic
floods.In
contributes
development
IoT-based
technologies
systems
context
mitigation.
