Practice, progress, and proficiency in sustainability,
Год журнала:
2024,
Номер
unknown, С. 157 - 184
Опубликована: Ноя. 1, 2024
Artificial
Intelligence
(AI)
transforms
environmental
conservation
by
enhancing
sustainability
and
efficiency
in
addressing
critical
challenges.
However,
AI
must
be
regulated
within
a
robust
policy,
governance,
law
framework
to
harness
its
full
potential.
This
paper
explores
the
complex
interaction
of
these
elements
regulating
for
sustainable
protection.
Through
doctrinal
methodology,
it
examines
legal
texts,
policies,
governance
structures
assess
their
adequacy
guiding
applications
ecological
contexts.
The
findings
reveal
significant
gaps
current
frameworks,
underscoring
need
integrated,
enforceable
guidelines
that
ensure
ethical
deployment.
research
concludes
advocating
comprehensive
regulatory
tools
align
with
goals.
World Journal of Advanced Research and Reviews,
Год журнала:
2024,
Номер
21(1), С. 161 - 171
Опубликована: Янв. 4, 2024
The
rapid
increase
in
human
activities
is
causing
significant
damage
to
our
planet's
ecosystems,
necessitating
innovative
solutions
preserve
biodiversity
and
counteract
ecological
threats.
Artificial
Intelligence
(AI)
has
emerged
as
a
transformative
force,
providing
unparalleled
capabilities
for
environmental
monitoring
conservation.
This
research
paper
explores
the
applications
of
AI
ecosystem
management,
including
wildlife
tracking,
habitat
assessment,
analysis,
natural
disaster
prediction.
AI's
role
conservation
includes
resource
conservation,
species
identification.
algorithms
analyze
camera
trap
footage,
drone
imagery,
GPS
data
identify
estimate
population
sizes,
leading
improved
anti-poaching
efforts
enhanced
protection
diverse
species.
Habitat
assessment
involve
AI-powered
image
which
aids
assessing
forest
health,
detecting
deforestation,
identifying
areas
need
restoration.
Biodiversity
analysis
identification
are
achieved
through
that
acoustic
recordings,
DNA
(eDNA),
footage.
These
innovations
different
species,
assess
levels,
even
discover
new
or
endangered
flood
prediction
systems
provide
early
warnings,
empowering
communities
with
better
preparedness
evacuation
efforts.
Challenges,
such
quality
availability,
algorithmic
bias,
infrastructure
limitations,
acknowledged
opportunities
growth
improvement.
In
policy
regulation,
advocates
clear
frameworks
prioritizing
privacy
security,
transparency,
equitable
access.
Responsible
development
ethical
use
emphasized
foundational
pillars,
ensuring
integration
into
aligns
principles
fairness,
societal
benefit.
Philosophical Transactions of the Royal Society B Biological Sciences,
Год журнала:
2025,
Номер
380(1925)
Опубликована: Май 1, 2025
The
behaviour
of
both
humans
and
wildlife
is
central
to
the
conservation
biodiversity
because
requires
human
actions
at
multiple
scales.
In
species
with
evidence
socially
learned
culture,
juxtaposition
animal
culture
increases
complexity
human-wildlife
interactions
their
investigation
but
also
offers
opportunities
mitigate
negative
interactions.
this
paper,
we
consider
language
used
analyse
human-animal
review
effect
behaviours
on
those
We
investigate
how
knowledge
theory
from
behavioural
studies
can
be
negotiate
complex
between
wildlife,
providing
specific
examples
mined
for
developing
policies
regarding
highlight
that
are
such
a
key
target
conservation.
Integrating
social
learning
into
research
scope
leverage
gaps,
misconceptions
concerns
targeted,
relevant
meaningful.This
article
part
theme
issue
'Animal
culture:
in
changing
world'.
Sensors,
Год журнала:
2025,
Номер
25(2), С. 352 - 352
Опубликована: Янв. 9, 2025
Elephant
sound
identification
is
crucial
in
wildlife
conservation
and
ecological
research.
The
of
elephant
vocalizations
provides
insights
into
the
behavior,
social
dynamics,
emotional
expressions,
leading
to
conservation.
This
study
addresses
classification
utilizing
raw
audio
processing.
Our
focus
lies
on
exploring
lightweight
models
suitable
for
deployment
resource-costrained
edge
devices,
including
MobileNet,
YAMNET,
RawNet,
alongside
introducing
a
novel
model
termed
ElephantCallerNet.
Notably,
our
investigation
reveals
that
proposed
ElephantCallerNet
achieves
an
impressive
accuracy
89%
classifying
directly
without
converting
it
spectrograms.
Leveraging
Bayesian
optimization
techniques,
we
fine-tuned
parameters
such
as
learning
rate,
dropout,
kernel
size,
thereby
enhancing
model's
performance.
Moreover,
scrutinized
efficacy
spectrogram-based
training,
prevalent
approach
animal
classification.
Through
comparative
analysis,
processing
outperforms
methods.
In
contrast
other
literature
primarily
single
caller
type
or
binary
identifies
whether
voice
not,
solution
designed
classify
three
distinct
caller-types
namely
roar,
rumble,
trumpet.
Abstract
In
recent
years,
the
integration
of
artificial
intelligence
(AI)
has
markedly
bolstered
productivity,
especially
in
agriculture,
mitigating
environmental
impacts
like
greenhouse
gas
emissions.
This
shift
employs
a
range
tech,
IT,
sensors,
robotics,
and
AI,
boosting
output
while
curbing
negative
effects.
Challenges
persist,
notably
food
scarcity
climate
threats
for
growing
global
population.
By
2050,
two
billion
more
people
will
need
sustenance,
necessitating
urgent
agricultural
innovation.
article
reviewed
databases
from
1985
to
2023
(Google
Scholar,
Scopus,
ISI
Web
Knowledge),
analyzing
AI’s
role
agriculture.
Keywords
precision
feeding,
welfare,
animal
husbandry,
management
were
used
systematic
literature
review.
Findings
highlight
pivotal
addressing
shortages.
Investment
emerging
is
crucial
sustainable
supply.
Advances in environmental engineering and green technologies book series,
Год журнала:
2025,
Номер
unknown, С. 19 - 48
Опубликована: Янв. 10, 2025
The
integration
of
artificial
intelligence
(AI)
into
wildlife
conservation
has
revolutionized
methodologies
for
monitoring
species,
enhancing
habitat
management,
and
combating
poaching.
This
chapter
examines
various
AI
applications
that
contribute
to
the
protection
preservation
biodiversity.
Remote
sensing
technologies,
powered
by
machine
learning
algorithms,
assist
in
assessing
health
tracking
changes
over
time.
AI-driven
image
recognition
tools
enable
identification
individual
animals
from
camera
trap
photos,
facilitating
more
accurate
population
estimates
behavioral
studies.
Moreover,
predictive
analytics
play
a
crucial
role
forecasting
human-wildlife
conflicts
informing
proactive
management
strategies.
synthesis
technologies
demonstrates
their
potential
enhance
efforts,
optimize
resource
allocation,
ultimately
foster
effective
initiatives.
ongoing
advancement
this
field
promises
create
innovative
solutions
some
most
pressing
challenges.
