Processes,
Journal Year:
2022,
Volume and Issue:
10(11), P. 2462 - 2462
Published: Nov. 21, 2022
Water
is
a
precious
resource
that
can
be
intelligently
managed.
Effective
water
usage
demands
computerized
home
supply
management
in
culture
where
tanks,
motors,
and
pumps
are
ubiquitous.
crucial
for
the
government
citizens
countries
like
Saudi
Arabia.
The
issue
providing
constant,
high-quality,
low-cost
supply.
This
study
introduces
smart
(IoT-SWM)
system
may
used
structures
do
not
have
access
to
constant
but
instead
stored
enormous
tanks
underneath.
GSM
module
collects
use
data
from
each
community
transmits
it
cloud,
analyzed.
A
grid
hybrid
application
uses
an
inspection
mode
identify
leaks
measure
resulting
height
differences
keep
track
of
tank’s
level.
automatically
deactivates
affected
section
after
detecting
any
shortage
or
malfunction
mechanism,
such
as
broken
valves,
pumps,
pipes.
It
sends
emergency
signal
building
managers.
monitors
essential
quality
elements
regularly,
if
they
fall
below
acceptable
levels,
warning
signals
management,
who
take
action.
Over
extended
period,
monitored
recorded
all
metrics.
restarts
when
pump
has
been
reconnected
alert.
As
result,
suggested
excellent
replacement
Arabia’s
mechanically
operated
system.
Water Science & Technology,
Journal Year:
2020,
Volume and Issue:
82(12), P. 2635 - 2670
Published: Aug. 5, 2020
Abstract
The
global
volume
of
digital
data
is
expected
to
reach
175
zettabytes
by
2025.
volume,
variety
and
velocity
water-related
are
increasing
due
large-scale
sensor
networks
increased
attention
topics
such
as
disaster
response,
water
resources
management,
climate
change.
Combined
with
the
growing
availability
computational
popularity
deep
learning,
these
transformed
into
actionable
practical
knowledge,
revolutionizing
industry.
In
this
article,
a
systematic
review
literature
conducted
identify
existing
research
that
incorporates
learning
methods
in
sector,
regard
monitoring,
governance
communication
resources.
study
provides
comprehensive
state-of-the-art
approaches
used
industry
for
generation,
prediction,
enhancement,
classification
tasks,
serves
guide
how
utilize
available
future
challenges.
Key
issues
challenges
application
techniques
domain
discussed,
including
ethics
technologies
decision-making
management
governance.
Finally,
we
provide
recommendations
directions
models
hydrology
Sustainable Cities and Society,
Journal Year:
2021,
Volume and Issue:
76, P. 103442 - 103442
Published: Oct. 19, 2021
Smart
cities
are
an
innovate
concept
for
managing
urban
to
enhance
sustainability
and
increase
quality
of
life
citizens.
Although
water
infrastructure
(UWI)
performs
important
functions
in
a
city
(e.g.,
supply
drinking
water),
information
communication
technologies
(ICT)
system-wide
management
network-based
UWI
not
yet
widely
deployed.
Therefore,
this
review
summarises
first
both
existing
potential
applications
related
UWI,
characterised
by
different
spatial
temporal
resolution
measurement
control
data.
Second,
comprehensive
analysis
ICT
is
provided,
which
extended
with
exemplary
the
field.
The
reveals
that
coordination
between
intended
application
usable
technology
required
realise
efficient
monitoring
network
field
networks.
To
overcome
limitation,
detailed
framework
developed,
can
be
used
researcher,
operators,
stakeholder
identify
suitable
or
determine
possible
system.
Following,
applicability
demonstrated
selected
examples.
As
also
indicates,
integrated
approach
towards
smart
requires
combination
satisfy
all
specifications.
Information,
Journal Year:
2024,
Volume and Issue:
15(10), P. 596 - 596
Published: Sept. 30, 2024
This
paper
presents
a
novel
framework,
artificial
intelligence-enabled
intelligent
assistant
(AIIA),
for
personalized
and
adaptive
learning
in
higher
education.
The
AIIA
system
leverages
advanced
AI
natural
language
processing
(NLP)
techniques
to
create
an
interactive
engaging
platform.
platform
is
engineered
reduce
cognitive
load
on
learners
by
providing
easy
access
information,
facilitating
knowledge
assessment,
delivering
support
tailored
individual
needs
styles.
AIIA’s
capabilities
include
understanding
responding
student
inquiries,
generating
quizzes
flashcards,
offering
pathways.
research
findings
have
the
potential
significantly
impact
design,
implementation,
evaluation
of
AI-enabled
virtual
teaching
assistants
(VTAs)
education,
informing
development
innovative
educational
tools
that
can
enhance
outcomes,
engagement,
satisfaction.
methodology,
architecture,
services,
integration
with
management
systems
(LMSs)
while
discussing
challenges,
limitations,
future
directions
The
application
of
Artificial
Intelligence
(AI)
across
a
wide
range
domains
comes
with
both
high
expectations
its
benefits
and
dire
predictions
misuse.
While
AI
systems
have
largely
been
driven
by
technology-centered
design
approach,
the
potential
societal
consequences
mobilized
HCI
researchers
towards
researching
human-centered
artificial
intelligence
(HCAI).
However,
there
remains
considerable
ambiguity
about
what
it
means
to
frame,
evaluate
HCAI.
This
paper
presents
critical
review
large
corpus
peer-reviewed
literature
emerging
on
HCAI
in
order
characterize
community
is
defining
as
Our
contributes
an
overview
map
research
based
work
that
explicitly
mentions
terms
'human-centered
intelligence'
or
machine
learning'
their
variations,
suggests
future
challenges
directions.
reveals
breadth
happening
HCAI,
established
clusters
areas
Interaction
Ethical
AI.
new
definition
calls
for
greater
collaboration
between
research,
constructs.
International Journal of Educational Technology in Higher Education,
Journal Year:
2023,
Volume and Issue:
20(1)
Published: July 23, 2023
Abstract
Miscommunication
between
instructors
and
students
is
a
significant
obstacle
to
post-secondary
learning.
Students
may
skip
office
hours
due
insecurities
or
scheduling
conflicts,
which
can
lead
missed
opportunities
for
questions.
To
support
self-paced
learning
encourage
creative
thinking
skills,
academic
institutions
must
redefine
their
approach
education
by
offering
flexible
educational
pathways
that
recognize
continuous
this
end,
we
developed
an
AI-augmented
intelligent
assistance
framework
based
on
powerful
language
model
(i.e.,
GPT-3)
automatically
generates
course-specific
assistants
regardless
of
discipline
level.
The
virtual
teaching
assistant
(TA)
system,
at
the
core
our
framework,
serves
as
voice-enabled
helper
capable
answering
wide
range
questions,
from
curriculum
logistics
course
policies.
By
providing
with
easy
access
information,
TA
help
improve
engagement
reduce
barriers
At
same
time,
it
also
logistical
workload
TAs,
freeing
up
time
focus
other
aspects
supporting
students.
Its
GPT-3-based
knowledge
discovery
component
generalized
system
architecture
are
presented
accompanied
methodical
evaluation
system’s
accuracy
performance.
