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

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

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