Leveraging edge artificial intelligence for sustainable agriculture

Journal article (2024)

Authors

Moussa El Jarroudi Sart Tilman B52
Louis Kouadio Centre for Applied Climate Sciences, W. Africa Rice Devmt. Association
Philippe Delfosse University of Luxembourg
Clive H. Bock USDA ARS U.S. Horticultural Research Laboratory
Anne Katrin Mahlein Institute of Sugar Beet Research
Xavier Fettweis Sart Tilman B52
Benoit Mercatoris Sart Tilman B52, Gembloux Agro-Bio Tech
Frank Adams Lycée Technique Agricole
Jillian M. Lenné Fyvie Primary School
Said Hamdioui Computer Engineering - EEMCS , Quantum & Computer Engineering
S. Hamdioui Computer Engineering - EEMCS , Quantum & Computer Engineering
Research Group
Computer Engineering (EEMCS) (TU Delft)
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Published Date

2024

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Quantum & Computer Engineering

Research Group

Computer Engineering

Abstract

Effectively feeding a burgeoning world population is one of the main goals of sustainable agricultural practices. Digital technology, such as edge artificial intelligence (AI), has the potential to introduce substantial benefits to agriculture by enhancing farming practices that can improve agricultural production efficiency, yield, quality and safety. However, the adoption of edge AI faces several challenges, including the need for innovative and efficient edge AI solutions and greater investment in infrastructure and training, all compounded by various environmental, social and economic constraints. Here we provide a roadmap for leveraging edge AI at the intersection of food production and sustainability.

Files

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