Technologies driving the shift to smart farming: A review

As today's agriculture industry is facing numerous challenges, including climate changes, encroachment of the urban environment and lack of qualified farmers, there is a need for new practices to ensure sustainable agriculture and food supply. Consequently, there is an emphasis on upgrading the...

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Published in:IEEE sensors journal Vol. 23; no. 3; p. 1
Main Authors: Elbeheiry, Nabila, Balog, Robert S.
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Actuators
Automation
Best practice
Big Data
Capacitive sensors
Climate change
Data Analysis
Decision making
Deep Learning
Digital agriculture
Farmers
Farming
Internet of Things (IoT)
Irrigation Systems
Low Power Wide Area Network (LPWAN)
Machine Learning
Microcontrollers
Remote Monitoring
Robotics
Sensor phenomena and characterization
Sensors
Smart agriculture
Smart Farming
Temperature sensors
Urban environments
Wireless sensor networks
Wireless Sensor Networks (WSN)
ISSN:1530-437X, 1558-1748
Online Access:Get full text
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Summary:As today's agriculture industry is facing numerous challenges, including climate changes, encroachment of the urban environment and lack of qualified farmers, there is a need for new practices to ensure sustainable agriculture and food supply. Consequently, there is an emphasis on upgrading the farming practices by shifting towards Smart Farming (SF) - utilizing advanced information and communication technologies to improve the quantity and quality of the crop with minimal labor interference. SF has gained lots of interest in recent years utilizing a variety of technological innovations in the field, which imposes a challenge on farmers and technology integrators to identify the suitable technologies and best practices for a particular application. This paper provides a survey of the most recent SF scientific literature to identify common practices toward technology integration, challenges, and solutions. The survey was conducted on 588 papers published on the IEEE database following Cochrane methods to ensure appropriate analysis and interpretation of results. The papers' contributions were analyzed to identify necessary technologies that constitute SF, and consequently, research themes were identified. The identified themes are sensors, communication, big data, actuators and machines, and data analysis. Besides presenting an in-depth analysis of each identified theme, the paper discusses integrating more than one technology in systems to achieve independency. The most common SF systems are remote monitoring, autonomous, and intelligent decision-making systems.
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ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2022.3225183