Technology in Society,
Год журнала:
2023,
Номер
74, С. 102335 - 102335
Опубликована: Июль 27, 2023
Technological
advances
can
significantly
transform
agrarian
rural
areas
by
increasing
productivity
and
efficiency
while
reducing
labour
intensive
processes.
For
instance,
the
usage
of
Unmanned
Aerial
Vehicles
(UAVs)
offer
flexibility
collecting
real-time
information
crops
enabling
farmers
to
take
timely
decisions.
However,
little
is
known
about
barriers
adoption
such
technologies
in
emerging
economies
like
India.
Building
on
an
extensive
literature
review,
focussed
group
discussions,
field
visits,
impacting
are
identified
classified
into
technical,
social,
behavioural,
operational,
economic,
implementation
categories.
The
relevance
each
barrier
its
importance
evaluated
using
a
hybrid
multi-criteria
framework
built
theory
Fuzzy
Delphi
Analytical
Hierarchy
Process
identify
most
crucial
UAVs
implement
precision
agriculture
paper
suggests
new
avenues
for
accelerating
technology
economies.
Horticulturae,
Год журнала:
2023,
Номер
9(3), С. 399 - 399
Опубликована: Март 19, 2023
The
potential
of
precision
viticulture
has
been
highlighted
since
the
first
studies
performed
in
context
viticulture,
but
especially
last
decade
there
have
excellent
results
achieved
terms
innovation
and
simple
application.
deployment
new
sensors
for
vineyard
monitoring
is
set
to
increase
coming
years,
enabling
large
amounts
information
be
obtained.
However,
number
developed
great
amount
data
that
can
collected
are
not
always
easy
manage,
as
it
requires
cross-sectoral
expertise.
preliminary
section
review
presents
scenario
highlighting
its
possible
applications.
This
illustrates
types
their
operating
principles.
Remote
platforms
such
satellites,
unmanned
aerial
vehicles
(UAV)
proximal
also
presented.
Some
supervised
unsupervised
algorithms
used
object-based
image
segmentation
classification
(OBIA)
then
discussed,
well
a
description
some
vegetation
indices
(VI)
viticulture.
Photogrammetric
3D
canopy
modelling
using
dense
point
clouds
illustrated.
Finally,
machine
learning
deep
illustrated
processing
interpreting
big
understand
agronomic
physiological
status.
shows
perform
accurate
surveys
evaluations,
important
select
appropriate
sensor
or
platform,
so
post-processing
depend
on
type
collected.
Several
aspects
discussed
fundamental
understanding
implementation
variability
techniques.
evident
future,
artificial
intelligence
equipment
will
become
increasingly
relevant
detection
management
spatial
through
an
autonomous
approach.
Remote Sensing,
Год журнала:
2023,
Номер
15(17), С. 4273 - 4273
Опубликована: Авг. 31, 2023
Remote
sensing
technology
is
vital
for
precision
agriculture,
aiding
in
early
issue
detection,
resource
management,
and
environmentally
friendly
practices.
Recent
advances
remote
data
processing
have
propelled
unmanned
aerial
vehicles
(UAVs)
into
valuable
tools
obtaining
detailed
on
plant
diseases
with
high
spatial,
temporal,
spectral
resolution.
Given
the
growing
body
of
scholarly
research
centered
UAV-based
disease
a
comprehensive
review
analysis
current
studies
becomes
imperative
to
provide
panoramic
view
evolving
methodologies
monitoring
strategically
evaluate
potential
limitations
such
strategies.
This
study
undertakes
systematic
quantitative
literature
summarize
existing
discern
trends
applications
detection
monitoring.
Results
reveal
global
disparity
topic,
Asian
countries
being
top
contributing
(43
out
103
papers).
World
regions
as
Oceania
Africa
exhibit
comparatively
lesser
representation.
To
date,
has
largely
focused
affecting
wheat,
sugar
beet,
potato,
maize,
grapevine.
Multispectral,
reg-green-blue,
hyperspectral
sensors
were
most
often
used
detect
identify
symptoms,
pointing
approaches
integrating
multiple
use
machine
learning
deep
techniques.
Future
should
prioritize
(i)
development
cost-effective
user-friendly
UAVs,
(ii)
integration
emerging
agricultural
technologies,
(iii)
improved
acquisition
efficiency
(iv)
diverse
testing
scenarios,
(v)
ethical
considerations
through
proper
regulations.
Computers and Electronics in Agriculture,
Год журнала:
2023,
Номер
211, С. 108051 - 108051
Опубликована: Июль 13, 2023
Grapevine
phenotyping
is
the
process
of
determining
physical
properties
(e.g.,
size,
shape,
and
number)
grape
bunches
berries.
information
provides
valuable
characteristics
to
monitor
sanitary
status
vine.
Knowing
number
dimensions
berries
at
an
early
stage
development
relevant
winegrowers
about
yield
be
harvested.
However,
counting
measuring
usually
done
manually,
which
laborious
time-consuming.
Previous
studies
have
attempted
implement
bunch
detection
on
red
in
vineyards
with
leaf
removal
surveys
been
using
ground
vehicles
handled
cameras.
Unmanned
Aerial
Vehicles
(UAV)
mounted
RGB
cameras,
along
computer
vision
techniques
offer
a
cheap,
robust,
timesaving
alternative.
Therefore,
Multi-object
tracking
segmentation
(MOTS)
utilized
this
study
determine
traits
individual
white
from
videos
obtained
UAV
acquired
over
commercial
vineyard
high
density
leaves.
To
achieve
goal
two
datasets
labelled
images
measurements
were
created
made
available
public
repository.
PointTrack
algorithm
was
used
for
detecting
bunches,
instance
algorithms
-
YOLACT
Spatial
Embeddings
compared
finding
most
suitable
approach
detect
It
found
that
performs
adequately
cluster
MODSA
93.85.
For
tracking,
results
not
sufficient
when
trained
679
frames.This
automated
pipeline
extraction
several
described
by
International
Organization
Vine
Wine
(OIV)
descriptors.
The
selected
OIV
descriptors
are
length,
width,
shape
(codes
202,
203,
208,
respectively)
berry
220,
221,
223,
respectively).
Lastly,
comparison
regarding
detected
per
indicated
assessed
more
accurately
(79.5%)
than
(44.6%).
Remote Sensing,
Год журнала:
2023,
Номер
16(1), С. 149 - 149
Опубликована: Дек. 29, 2023
With
the
rapid
development
of
object
detection
technology
for
unmanned
aerial
vehicles
(UAVs),
it
is
convenient
to
collect
data
from
UAV
photographs.
They
have
a
wide
range
applications
in
several
fields,
such
as
monitoring,
geological
exploration,
precision
agriculture,
and
disaster
early
warning.
In
recent
years,
many
methods
based
on
artificial
intelligence
been
proposed
detection,
deep
learning
key
area
this
field.
Significant
progress
has
achieved
deep-learning-based
detection.
Thus,
paper
presents
review
research
This
survey
provides
an
overview
UAVs
summarizes
UAVs.
addition,
issues
are
analyzed,
small
under
complex
backgrounds,
rotation,
scale
change,
category
imbalance
problems.
Then,
some
representative
solutions
these
summarized.
Finally,
future
directions
field
discussed.
Technology in Society,
Год журнала:
2023,
Номер
74, С. 102335 - 102335
Опубликована: Июль 27, 2023
Technological
advances
can
significantly
transform
agrarian
rural
areas
by
increasing
productivity
and
efficiency
while
reducing
labour
intensive
processes.
For
instance,
the
usage
of
Unmanned
Aerial
Vehicles
(UAVs)
offer
flexibility
collecting
real-time
information
crops
enabling
farmers
to
take
timely
decisions.
However,
little
is
known
about
barriers
adoption
such
technologies
in
emerging
economies
like
India.
Building
on
an
extensive
literature
review,
focussed
group
discussions,
field
visits,
impacting
are
identified
classified
into
technical,
social,
behavioural,
operational,
economic,
implementation
categories.
The
relevance
each
barrier
its
importance
evaluated
using
a
hybrid
multi-criteria
framework
built
theory
Fuzzy
Delphi
Analytical
Hierarchy
Process
identify
most
crucial
UAVs
implement
precision
agriculture
paper
suggests
new
avenues
for
accelerating
technology
economies.
