Leveraging edge artificial intelligence for sustainable agriculture
Article
Article Title | Leveraging edge artificial intelligence for sustainable agriculture |
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ERA Journal ID | 213764 |
Article Category | Article |
Authors | El Jarroudi, Moussa, Kouadio, Louis, Delfosse, Philippe, Bock, Clive H., Mahlein, Anne-Katrin, Fettweis, Xavier, Mercatoris, Benoit, Adams, Frank, Lenné, Jillian M. and Hamdioui, Said |
Journal Title | Nature Sustainability |
Journal Citation | 7, pp. 846-854 |
Number of Pages | 9 |
Year | 2024 |
Publisher | Nature Publishing Group |
Place of Publication | United Kingdom |
ISSN | 2398-9629 |
Digital Object Identifier (DOI) | https://doi.org/10.1038/s41893-024-01352-4 |
Web Address (URL) | https://www.nature.com/articles/s41893-024-01352-4 |
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. |
Keywords | artificial intelligence; sustainable agriculture |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 3002. Agriculture, land and farm management |
3004. Crop and pasture production | |
4602. Artificial intelligence | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Liege, Belgium |
Centre for Applied Climate Sciences | |
Institute for Life Sciences and the Environment | |
University of Luxembourg | |
Department of Agriculture, United States | |
Institute of Sugar Beet Research, Germany | |
Lycée Technique Agricole, Luxembourg | |
North Oldmoss Croft, United Kingdom | |
Delft University of Technology, Netherlands |
https://research.usq.edu.au/item/z8360/leveraging-edge-artificial-intelligence-for-sustainable-agriculture
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