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  5. DIGITAL TWIN: ORCHARD MANAGEMENT USING UAV
 
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DIGITAL TWIN: ORCHARD MANAGEMENT USING UAV

Journal
ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference
ISSN
2256-070X
Date Issued
2023
Author(s)
Zarembo, Imants 
Rezekne Academy of Technologies 
Kodors, Sergejs
Rezekne Academy of Technologies 
Apeināns, Ilmārs
Rezekne Academy of Technologies 
Gunārs Lācis
Institute of Horticulture (LatHort)Dobele, Latvia
Daina Feldmane
Institute of Horticulture (LatHort)Dobele, Latvia
Edgars Rubauskis
Institute of Horticulture (LatHort)Dobele, Latvia
DOI
10.17770/etr2023vol1.7290
Abstract
Orchard management can benefit greatly from the use of modern technology to reach higher yields, decrease costs and achieve more sustainable farming. Implementation or such a smart farming approach into orchard management can be realised via application of unmanned aerial vehicles (UAV) for data collection and artificial intelligence (AI) for yield estimation and forecasting. On top of that, a digital twin of the orchard can be implemented to represent the physical system of the orchard in the digital format allowing implement modern data-driven decision-making based on fruit-growing automation.The aim of this study is to present a digital twin based on application of UAV and AI for orchard management that is being developed as part of a research project lzp-2021/1-0134. At this moment, we are developing a user-centred design which is oriented to satisfy horticulture specialists’ needs for an autonomous monitoring system and to help them in decision-making. Within the framework of this study an enterprise model of orchard management is designed, which supports the digital twin concept and provides autonomous orchard monitoring. The study is scoped with subjects: apples, pears and cherries, and yield management based on orchard monitoring using UAV.
Subjects
  • cyber-physical syst...

  • digital twin

  • data-based decision-m...

  • smart horticulture

File(s)
 DIGITAL TWIN_ ORCHARD MANAGEMENT USING UAV.pdf (1.58 MB)
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0
Acquisition Date
Jan 12, 2024
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