Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses

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 b...

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Main Authors: Levonevskiy Dmitriy, Zhukova Nataly, Kovalevsky Vladislav
Format: Article
Language:English
Published: EDP Sciences 2023-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/29/e3sconf_rse-ii-2023_01011.pdf
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author Levonevskiy Dmitriy
Zhukova Nataly
Kovalevsky Vladislav
author_facet Levonevskiy Dmitriy
Zhukova Nataly
Kovalevsky Vladislav
author_sort Levonevskiy Dmitriy
collection DOAJ
description 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.
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spelling doaj.art-d936a89fec89451cbdb87f51062ae3e32023-06-09T09:12:35ZengEDP SciencesE3S Web of Conferences2267-12422023-01-013920101110.1051/e3sconf/202339201011e3sconf_rse-ii-2023_01011Proactive monitoring and analysis of technological processes of growing crops in automated greenhousesLevonevskiy Dmitriy0Zhukova Nataly1Kovalevsky Vladislav2St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS)St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS)St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS)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.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/29/e3sconf_rse-ii-2023_01011.pdf
spellingShingle Levonevskiy Dmitriy
Zhukova Nataly
Kovalevsky Vladislav
Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
E3S Web of Conferences
title Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
title_full Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
title_fullStr Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
title_full_unstemmed Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
title_short Proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
title_sort proactive monitoring and analysis of technological processes of growing crops in automated greenhouses
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/29/e3sconf_rse-ii-2023_01011.pdf
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