Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses

Mihai Frangulea, Christos Pantos, Mario Valerio Giuffrida, Joao Valente

Precision Agriculture (2021)

Frangulea, M., Pantos, C., Giuffrida, V., Valente, J. (2021). Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses. In Precision agriculture’21 (pp. 99-102). Wageningen Academic Publishers.

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@incollection{frangulea202,
  title={Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses},
  author={Frangulea, M and Pantos, C and Giuffrida, V and Valente, J},
  booktitle={Precision agriculture’21},
  pages={99--102},
  year={2021},
  publisher={Wageningen Academic Publishers}
}

Abstract:

A tool for plant phenotyping is proposed to aid users in analyzing data on-demand. This tool is web-based and runs deep learning models. The current study focuses on the development of this tool, as well as obtaining a plant dataset to train a neural network. Furthermore, smartphone and drone imagery are used to test the derived model. The results demonstrate how data generalization can be reached through participatory sensing. Finally, drones show potential as being a fast solution for acquiring sensory information within greenhouses.