Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey
IEEE Access,
Journal Year:
2023,
Volume and Issue:
11, P. 145813 - 145852
Published: Jan. 1, 2023
The
increasing
food
scarcity
necessitates
sustainable
agriculture
achieved
through
automation
to
meet
the
growing
demand.
Integrating
Internet
of
Things
(IoT)
and
Wireless
Sensor
Networks
(WSNs)
is
crucial
in
enhancing
production
across
various
agricultural
domains,
encompassing
irrigation,
soil
moisture
monitoring,
fertilizer
optimization
control,
early-stage
pest
crop
disease
management,
energy
conservation.
application
protocols
such
as
ZigBee,
WiFi,
SigFox,
LoRaWAN
are
commonly
employed
collect
real-time
data
for
monitoring
purposes.
Embracing
advanced
technology
imperative
ensure
efficient
annual
production.
Therefore,
this
study
emphasizes
a
comprehensive,
future-oriented
approach,
delving
into
IoT-WSNs,
wireless
network
protocols,
their
applications
since
2019.
It
thoroughly
discusses
overview
IoT
WSNs,
architectures
summarization
protocols.
Furthermore,
addresses
recent
issues
challenges
related
IoT-WSNs
proposes
mitigation
strategies.
provides
clear
recommendations
future,
emphasizing
integration
aiming
contribute
future
development
smart
systems.
Language: Английский
Traditional and Blockchain Based IoT and IIoT Security in the Context of Agriculture: A Survey
Rishikesh,
No information about this author
Ditipriya Sinha
No information about this author
Wireless Personal Communications,
Journal Year:
2023,
Volume and Issue:
133(4), P. 2267 - 2295
Published: Dec. 1, 2023
Language: Английский
Systematic Mapping Study of Sales Forecasting: Methods, Trends, and Future Directions
Hamid Ahaggach,
No information about this author
Lylia Abrouk,
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Éric Lebon
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et al.
Forecasting,
Journal Year:
2024,
Volume and Issue:
6(3), P. 502 - 532
Published: July 5, 2024
In
a
dynamic
business
environment,
the
accuracy
of
sales
forecasts
plays
pivotal
role
in
strategic
decision
making
and
resource
allocation.
This
article
offers
systematic
review
existing
literature
on
techniques
methodologies
used
forecasting,
especially
forecasting
across
various
domains,
aiming
to
provide
nuanced
understanding
field.
Our
study
examines
from
2013
2023,
identifying
key
their
evolution
over
time.
The
methodology
involves
detailed
analysis
516
articles,
categorized
into
classical
qualitative
approaches,
traditional
statistical
methods,
machine
learning
models,
deep
techniques,
hybrid
approaches.
results
highlight
significant
shift
towards
advanced
with
experiencing
an
explosive
increase
adoption.
popularity
these
models
has
surged,
as
evidenced
by
rise
10
articles
110
2023.
growth
underscores
growing
prominence
effectiveness
handling
complex
time
series
data.
Additionally,
we
explore
challenges
limitations
that
influence
accuracy,
focusing
market
structures
benefits
extensive
data
availability.
Language: Английский