학술논문

Agro-Technological Systems in Traditional Agriculture Assistance: A Systematic Review
Document Type
Periodical
Source
IEEE Access Access, IEEE. 11:123047-123069 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Production
Statistics
Sociology
Systematics
Food security
Smart agriculture
Precision engineering
Agricultural applications
food security
precision agriculture
Language
ISSN
2169-3536
Abstract
Guaranteeing food security from agriculture in an uncertain context, derived from the effects of multiple factors, is a challenge. Traditional agricultural production is the one that faces the greatest challenges, derived from the scarce evolution in agricultural practices, despite being the one that contributes the most to the availability of food, at 80%. This systematic review aims to identify and analyze agrotechnological systems belonging to precision agriculture, which may be potentially adaptable to traditional rural agriculture. Contributions that improved crop yields from scientific and technological studies were analyzed. The PRISMA statement was used as a formal outline to collect and analyze 114 studies from the period 2018-2023. From the review, it was identified that there is a growing trend in the adoption of intelligent systems that help producers in the management of crops, accentuated in the increase of crop yield, in the determination of product quality, and in the management of water resources, mainly. Likewise, it was identified that the preponderant approach is the monitoring and control of crop development. This is achieved through emerging technologies, such as the Internet of Things, artificial intelligence, and machine learning, with information mainly collected by sensors embedded in drones, algorithms, decision support systems, sensors, and Arduino technology systems. Finally, this review shows that there are five viable systems that can be adapted to traditional agriculture to strengthen agricultural production. Therefore, the adoption of scientific-technological contributions from precision agriculture contributes to ensuring food security.