Electronics,
Journal Year:
2025,
Volume and Issue:
14(4), P. 696 - 696
Published: Feb. 11, 2025
The
integration
of
artificial
intelligence
(AI)
agents
with
the
Internet
Things
(IoT)
has
marked
a
transformative
shift
in
environmental
monitoring
and
management,
enabling
advanced
data
gathering,
in-depth
analysis,
more
effective
decision
making.
This
comprehensive
literature
review
explores
AI
IoT
technologies
within
sciences,
particular
focus
on
applications
related
to
water
quality
climate
data.
methodology
involves
systematic
search
selection
relevant
studies,
followed
by
thematic,
meta-,
comparative
analyses
synthesize
current
research
trends,
benefits,
challenges,
gaps.
highlights
how
enhances
IoT’s
collection
capabilities
through
predictive
modeling,
real-time
analytics,
automated
making,
thereby
improving
accuracy,
timeliness,
efficiency
systems.
Key
benefits
identified
include
enhanced
precision,
cost
efficiency,
scalability,
facilitation
proactive
management.
Nevertheless,
this
encounters
substantial
obstacles,
including
issues
quality,
interoperability,
security,
technical
constraints,
ethical
concerns.
Future
developments
point
toward
enhancements
technologies,
incorporation
innovations
like
blockchain
edge
computing,
potential
formation
global
systems,
greater
public
involvement
citizen
science
initiatives.
Overcoming
these
challenges
embracing
new
technological
trends
could
enable
play
pivotal
role
strengthening
sustainability
resilience.
International Journal of Computational and Experimental Science and Engineering,
Journal Year:
2024,
Volume and Issue:
10(4)
Published: Oct. 20, 2024
Addressing
the
imperative
demand
for
accurate
water
quality
assessment,
this
paper
delves
into
application
of
deep
learning
techniques,
specifically
leveraging
IoT
sensor
datasets
classification
and
prediction
parameters.
The
utilization
LSTM
(Long
Short-Term
Memory)
models
navigates
intricacies
inherent
in
environmental
data,
emphasizing
balance
between
model
accuracy
interpretability.
This
equilibrium
is
achieved
through
deployment
interpretability
methods
such
as
LIME,
SHAP,
Anchor,
LORE.
Additionally,
incorporation
advanced
parameter
optimization
techniques
focuses
on
fine-tuning
essential
parameters
like
rates,
batch
sizes,
epochs
to
optimize
performance.
comprehensive
approach
ensures
not
only
precise
predictions
but
also
enhances
transparency
model,
addressing
critical
need
actionable
information
management.
research
significantly
contributes
convergence
learning,
IoT,
science,
offering
valuable
tools
informed
decision-making
while
highlighting
importance
optimal
performance
Ecotoxicology and Environmental Safety,
Journal Year:
2025,
Volume and Issue:
291, P. 117817 - 117817
Published: Feb. 1, 2025
Two-dimensional
MXenes
are
promising
candidates
for
water
treatment
because
of
their
large
surface
area
(e.g.,
exceeding
1000
m²/g
certain
structures),
high
electrical
conductivity
>1000
S/m),
hydrophilicity,
and
chemical
stability.
Their
strong
sorption
selectivity
effective
reduction
capacity,
exemplified
by
heavy
metal
adsorption
efficiencies
95
%
in
several
studies,
coupled
with
facile
modification,
make
them
suitable
removing
diverse
contaminants.
Applications
include
the
removal
metals
achieving
>90
Pb(II)),
dye
demonstrating
>80
methylene
blue),
radioactive
waste
elimination.
Furthermore,
3D
MXene
architecture
exhibit
enhanced
performance
antibacterial
activities
against
bacteria),
desalination
rejection
percentage,
photocatalytic
degradation
organic
However,
challenges
have
remained,
which
necessitate
further
investigation
into
toxicity
assessing
effects
on
aquatic
organisms),
scalability,
cost-effectiveness
large-scale
production.
This
review
summarizes
recent
advancements
MXene-based
functional
materials
wastewater
remediation,
critically
analyzing
both
potential
limitations.
IntechOpen eBooks,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 5, 2025
Water,
sometimes
referred
to
as
the
‘matrix
of
life’,
highlights
fundamental
significance
life’s
ecosystem.
However,
water
pollution
creates
substantial
worldwide
concerns,
jeopardising
access
safe
drinking
and
impeding
progress
towards
Sustainable
Development
Goals
(SDGs).
Real-time
monitoring
(RTM)
systems,
which
use
modern
sensor
technology
data
analytics,
present
a
possible
answer
these
issues.
The
study
examines
challenges
presented
by
issues
such
scarcity,
insufficient
sanitary
infrastructure.
This
emphasised
function
RTM
in
management,
emphasising
its
benefits
for
improving
quality
monitoring,
supporting
effective
management
strategies
protecting
resources.
Furthermore,
it
investigates
Internet
Things
(IoT)
devices
remote
sensing
techniques
detection,
their
ability
give
real-time
data,
increase
capabilities
promote
informed
decision-making.
chapter
also
advanced
sensors
(chemical
sensors,
smart
satellite
sensors),
analytics
visualisation
approaches
enhanced
decision-making
resource
management.
Overall,
RTM,
when
combined
with
IoT
technologies,
provides
holistic
strategy
addressing
pollution,
mitigating
effects
promoting
sustainable
practices.
