DAAfrica'2024: Data Science for Agriculture in Africa Paulin Melatagia Yonta 1 2 Mathieu Roche 0 2 CIRAD, UMR TETIS , F-34398 Montpellier , France / TETIS, Université de Montpellier , AgroParisTech, CIRAD, INRAE, Montpellier , France University of Yaoundé I , Cameroun / IRD, UMMISCO, F-93143, Bondy , France Paulin Melatagia Yonta, University of Yaounde I, Cameroun - co-chair • Mathieu Roche, CIRAD, TETIS, Montpellier, France - co-chair • Marcellin Atemkeng, Rhodes University , South Africa • Sandrine Auzoux, CIRAD, AIDA, Saint-Denis, La Réunion, France • Roberto Interdonato, CIRAD, TETIS, Montpellier , France • Julien Sarron, CIRAD, HortSys, Madagascar • Mehtab Alam Syed, CIRAD, TETIS, Montpellier , France • Maguelonne Teisseire, INRAE, TETIS, Montpellier , France

Data science in agriculture has evolved with the increasing accessibility of data to farmers, which allows them to analyze and make decisions. Today, new technologies such as the Internet of Things (IoT) enable the collection and storage of farm and environmental data (e.g., soil data and water data) in dedicated databases and/or data warehouses. These agricultural data can be combined with other data sources (e.g., remote sensing, weather stations, and social media), highlighting the need to address new challenges, such as the use of heterogeneous data.

 eol>Data science agriculture Preface Papers in these CEUR proceedings

Scientific Committee

 Acknowledgments

This workshop was supported by The African Society in Digital Science (ASDS) - https://asds.africa/.

This workshop was partially funded by the French National Research Agency under the Investments for the Future Programme #DigitAg, referred to as ANR-16-CONV-0004 and the EU grant 874850 MOOD.

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