Abstract
Aiming at the difficulties of soil moisture control in greenhouse, including soil moisture perception and dynamic prediction with spatiotemporal properties, the sprinkler irrigation event model in the greenhouse based on the CPS spatiotemporal event model is analyzed; In allusion to the spatial variability of greenhouse soil, a layout algorithm of greenhouse soil moisture sensors combining regular mesh and Delaunay triangulation is designed; Meanwhile, aiming at the strong time lag of the soil moisture change in the greenhouse, an RBF neural network dynamic prediction model is designed based on Delaunay triangulation optimization algorithm.
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Acknowledgements
This research was supported by “Digital Agriculture” Emerging Cross Key Discipline of Jilin Province, Smart Agricultural Engineering Research Center of Jilin Province and Jilin Agricultural Science and Technology University Youth Fund Project (JLASTU Contract Number: 20190354).
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Bo, X., Tang, Y. (2021). Dynamic Prediction Model of Greenhouse Soil Moisture Driven by CPS Spatiotemporal Events. In: Abawajy, J., Choo, KK., Xu, Z., Atiquzzaman, M. (eds) 2020 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2020. Advances in Intelligent Systems and Computing, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-030-53980-1_96
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DOI: https://doi.org/10.1007/978-3-030-53980-1_96
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