Issue |
E3S Web Conf.
Volume 392, 2023
II International Conference on Agriculture, Earth Remote Sensing and Environment (RSE-II-2023)
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Article Number | 01011 | |
Number of page(s) | 7 | |
Section | Issues of Sustainable Development of Agriculture | |
DOI | https://doi.org/10.1051/e3sconf/202339201011 | |
Published online | 06 June 2023 |
Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 39, 14th Line, St. Petersburg, 199178, Russia
* Corresponding author: levonevskij.d@iias.spb.su
Agricultural automation can reduce time and cost of crop production and minimize human factor that can lead to crop damage. This paper focuses on automating crop growth in compact greenhouses that automate several technological processes including periodic irrigation with a nutrient solution and a biofilter to ensure cyclic cultivation, measuring temperature, humidity, etc. Machine learning methods help estimate and predict operation parameters. During the experiment, the optimal methods and parameters were determined, and the best prediction accuracy could be achieved using the random forest method. Use of this approach enables proactive control of technological processes, ensures compliance with growing regulations and results in resources economy. Future research will develop a formal method for proactive process control.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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