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

Frangulea, M.; Pantos, C.; Giuffrida, V.; Valente, J.

Authors

M. Frangulea

C. Pantos

V. Giuffrida

J. Valente



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.

Citation

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 (493-500). https://doi.org/10.3920/978-90-8686-916-9_59

Conference Name 13th European Conference on Precision Agriculture
Conference Location Budapest, Hungary
Start Date Jul 18, 2021
End Date Jul 22, 2021
Online Publication Date Jun 25, 2021
Publication Date Jul 19, 2021
Deposit Date Oct 27, 2022
Publisher Wageningen Academic Publishers
Pages 493-500
Book Title Precision agriculture ’21
ISBN 978-90-8686-363-1
DOI https://doi.org/10.3920/978-90-8686-916-9_59
Keywords kale, smartphone, drone, greenhouse, artificial intelligence
Public URL http://researchrepository.napier.ac.uk/Output/2940841