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Automatized Rapeseed Pest Detection and Management with Drones

  • Jere Kaivosoja*
  • , Ari Ronkainen
  • , Juho Hautsalo
  • , Juha Backman
  • , Raimo Linkolehto
  • , Miguel San Emeterio
  • , Juha Pekka Soininen
  • *Corresponding author for this work
  • Natural Resources Institute Finland (Luke)
  • ATOS IT Solutions and Services Iberia (ATOS)

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

Efficient oil seed pest management can be challenging. Invasive insect pests can destroy the whole yield, but the reduction of applied pesticides is well encouraged. Recent drone technologies provide new tools for the pest management. In this work, we studied possibilities for implementing drones for pest invasion scouting and for precision pesticide spraying for the rapeseed fields. We verified individual components for the pest imaging, pest identification, spraying application construction and for the spraying mission and made an implementation plan for the system automatization. In terms of custom automatization, the implementation of the spraying drone remains challenging.
Original languageEnglish
Title of host publicationROBOT 2022
Subtitle of host publication5th Iberian Robotics Conference - Advances in Robotics
EditorsDanilo Tardioli, Vicente Matellán, Guillermo Heredia, Manuel F. Silva, Lino Marques
PublisherSpringer
Pages427-437
ISBN (Print)978-3-03-121061-7
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Article in a conference publication
Event5th Iberian Robotics Conference, ROBOT 2022 - Zaragoza, Spain
Duration: 23 Nov 202225 Nov 2022

Publication series

SeriesLecture Notes in Networks and Systems
Volume590 LNNS
ISSN2367-3370

Conference

Conference5th Iberian Robotics Conference, ROBOT 2022
Country/TerritorySpain
CityZaragoza
Period23/11/2225/11/22

Funding

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017111. https://flexigrobots-h2020.eu/.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • FMIS
  • Image
  • ISOBUS
  • KML
  • Regulations
  • Spraying
  • UAV

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