Abstract
Agriculture is a booming market for several decades. Technological advances in this sector have produced promising results that can optimize profitability, productivity and sustainability. A technological revolution has taken place to meet industrial challenges. The development of the IoT has improved its sustainability and profitability by responding to digitization. New techniques emerge to improve the production process. Artificial Intelligence (AI) is presented as a science capable of replicating cognitive skills through machines. In this context, the main objective of this paper is building knowledge to guide researchers on AI advances and challenges in sustainable agricultural systems. It will be possible through the following specific steps: (a) Selecting a relevant Bibliographic Portfolio from the previous search on the Web Of Science database with time delineation of the last 11 years (from 2009 to 2019), and (b) Perform a bibliometric analysis of the bibliographic repertoire using the softwares Endnote X9®, Excel and to correlation analyses graphs will be diagrams with VosViewer®.
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Acknowledgements
The authors wish to thank the Federal University of Technology - Paraná for the financial support. The present study was developed under the financial support of the National Council for Scientific and Technological Development (CNPq).
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Przybysz, A.L., Gonçalves, M.A.A., Piekarskim, C.M., de Francisco, A.C. (2020). Recent Advances and Challenges in AI for Sustainable Agricultural Systems. In: Anisic, Z., Lalic, B., Gracanin, D. (eds) Proceedings on 25th International Joint Conference on Industrial Engineering and Operations Management – IJCIEOM. IJCIEOM 2019. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-43616-2_14
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