Advances in environmental engineering and green technologies book series,
Год журнала:
2024,
Номер
unknown, С. 231 - 246
Опубликована: Ноя. 29, 2024
The
protection
of
Earth's
ecology
and
balancing
rests
heavily
on
forest
preservation.
Issues
like
trafficking
wildlife,
illegal
logging,
deforestation
are
still
existing.
Conventional
methods
monitoring
techniques
safety
precautions
have
drawbacks
inefficient
to
address
these
ecological
problems.
In
the
present
era,
Artificial
Intelligence
is
advancing,
it
has
given
a
fresh
hope
in
preserving
forest.
chapter
examines
best
possible
use
preservation
concentrating
certain
situations
wildlife
conservation,
logging
surveillance
prediction
fire
forests.
intelligence
(AI)
technology
makes
available
greater
accuracy
efficiency
than
conventional
techniques,
allowing
for
quicker
detection
reaction
damage
activities.
AI
will
become
more
significant
future
because
additional
technical
developments
growth
application
areas,
opening
new
avenues
sustainable
Environmental Research Ecology,
Год журнала:
2024,
Номер
3(4), С. 043001 - 043001
Опубликована: Сен. 11, 2024
Abstract
Intact
native
forests
under
negligible
large-scale
human
pressures
(i.e.
high-integrity
forests)
are
critical
for
biodiversity
conservation.
However,
declining
worldwide
due
to
deforestation
and
forest
degradation.
Recognizing
the
importance
of
ecosystems
(including
forests),
Kunming-Montreal
Global
Biodiversity
Framework
(GBF)
has
directly
included
maintenance
restoration
ecosystem
integrity,
in
addition
extent,
its
goals
targets.
Yet,
headline
indicators
identified
help
nations
monitor
their
integrity
can
currently
track
changes
only
(1)
cover
or
(2)
risk
collapse
using
IUCN
Red
List
Ecosystems
(RLE).
These
unlikely
facilitate
monitoring
two
reasons.
First,
focusing
on
not
misses
impacts
anthropogenic
degradation
but
also
fail
detect
effect
positive
management
actions
enhancing
integrity.
Second,
as
measured
by
ordinal
RLE
index
(from
Least
Concern
Critically
Endangered)
makes
it
that
continuum
over
space
time
would
be
reported
nations.
Importantly,
many
biodiverse
African
Asian
remain
unassessed
with
RLE.
As
such,
will
likely
resort
alone
therefore
inadequately
report
progress
against
We
concur
indeed
vital
aspects
conservation
monitoring.
they
insufficient
specific
purpose
tracking
crucial
components
GBF’s
goals.
discuss
pitfalls
merely
cover,
a
outcome
current
indicators.
Augmenting
capture
change
absolute
area
along
toward
achieving
area-based
targets
related
both
extent
global
forests.
Advances in environmental engineering and green technologies book series,
Год журнала:
2024,
Номер
unknown, С. 247 - 272
Опубликована: Ноя. 29, 2024
Everyone
must
create
a
good
framework
to
handle
environmental,
financial,
and
social
issues
if
we
are
move
towards
sustainability.
Many
researchers
have
used
artificial
intelligence
(AI)
machine
learning
forward
sustainable
development
goals
by
building
highly
efficient
system
that
supports
circular
economy
aligns
the
needs
of
current
generation
while
safeguarding
capacities
future
generations.
Artificial
has
made
significant
progress
in
recent
years,
leading
changes
various
industries
including
healthcare,
transportation,
agriculture,
energy,
media.
This
paper
offers
comprehensive
analysis
junction
between
sustainability
together
with
several
possible
directions
for
next
investigation.
Advances in environmental engineering and green technologies book series,
Год журнала:
2024,
Номер
unknown, С. 49 - 68
Опубликована: Ноя. 29, 2024
AI
and
ML
have
opened
new
avenues
into
wildlife
conservation,
linking
efforts
worldwide
to
improve
forest
management.
However,
a
comprehensive
review
highlights
the
manifold
applications
of
these
technologies
for
biodiversity
conservation
natural
resource
These
are
automated
species
identification
population
monitoring
predict
habitat
degradation
anti-poaching
strategies,
all
contributing
immensely
preservation
Wildlife.
This
chapter
outlines
how
AI-powered
drones
sensor
networks
can
quickly
monitor
environments,
find
illegal
actions
as
they
happen,
collect
reams
data
on
behavior.
It
also
explores
opportunities
algorithms
study
intricate
ecological
inter-relationships,
climate
change
effects
&
optimize
restoration
management
activities.
provide
roadmap
great
promise
that
emergent
hold
in
providing
configurations
Wildlife
Conservation
Forest
Management
promote
Sustainable
future.
Advances in environmental engineering and green technologies book series,
Год журнала:
2024,
Номер
unknown, С. 69 - 92
Опубликована: Ноя. 29, 2024
General
enthusiasm
surrounding
the
possibilities
of
AI,
there
are
persistent
concerns
regarding
its
negative
impacts,
including
substantial
energy
consumption
and
issues
ethics.
The
evaluation
has
looked
at
several
uses
in
fields
building,
transportation,
healthcare,
manufacturing,
agriculture,
water.
Among
numerous
techniques
used
sustainability
regression,
DSS-based
(Decision
Support
System)
AI
models
RL
(Reinforcement
Learning)
most
often
ones.
assessment
also
provides
direction
on
industrial
sectors
using
strategies
to
include
ideas
sustainable
development
into
their
operations.
Remote Sensing,
Год журнала:
2024,
Номер
16(20), С. 3866 - 3866
Опубликована: Окт. 18, 2024
The
escalating
human
pressures
on
natural
ecosystems
necessitate
urgent
and
effective
conservation
strategies
to
safeguard
biodiversity
ecosystem
functions.
This
review
explored
current
techniques
for
mapping
pressure,
with
a
particular
focus
their
application
in
nature
conservation,
especially
within
protected
areas
(PAs).
Specifically,
we
analyzed
the
impacts
of
seven
major
types
PAs.
Additionally,
discussed
four
key
methods
including
land
use
intensity,
footprint,
digital
other
proxies,
examining
distinct
characteristics
respective
advantages
disadvantages.
our
research
pressure
assessing
its
suitability
applications
delineating
directions
future
work.
These
insights
contributed
better
support
management
