Machine Learning Applications in Agriculture: Current Trends, Challenges, and Future Perspectives

Machine Learning Applications in Agriculture: Current Trends, Challenges, and Future Perspectives

Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing are propelling the agricultural sector...

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Bibliographic Details
Main Authors: Sara Oleiro Araújo, Ricardo Silva Peres, José Cochicho Ramalho, Fernando Lidon, José Barata
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Agronomy
Subjects:
Agriculture 4.0
machine learning
PRISMA
systematic reviews and meta analytics
Online Access:https://www.mdpi.com/2073-4395/13/12/2976

Internet

https://www.mdpi.com/2073-4395/13/12/2976

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