• Lienīte Litavniece Research Institute for Business and Social Processes, Rezekne Academy of Technologies (LV)
  • Sergejs Kodors Institute of Engineering, Rezekne Academy of Technologies (LV)
  • Juta Dekšne Faculty of Economics and Management, Rezekne Academy of Technologies (LV)
  • Gunārs Lācis Institute of Horticulture, Dobele (LV)
  • Imants Zarembo Institute of Engineering, Rezekne Academy of Technologies (LV)
  • Antons Pacejs Institute of Engineering, Rezekne Academy of Technologies (LV)




decision-making, risk analysis, unmanned aerial vehicle, security, SORA


Risk analysis is an integral part of modern business management because successful business largely depends on the effective implementation of risk analysis. Agriculture is an important sector in the national economy, therefore Industry 4.0 increasingly provides digital solutions in orchard management, which facilitate and simplify decision-making in daily tasks. Meanwhile, unmanned aerial vehicles are applied as the agriculture sector's main monitoring and data acquisition tool. However, this means that it is necessary to pay attention to risk analysis due to the process of managing the orchard, where not only a person and the mechanized equipment controlled by him, which moves on the ground but also flying automated equipment participates. The purpose of the article is to perform the risk analysis for the survey and monitoring of orchards for yield estimation using unmanned aerial vehicles by considering commercial apple orchards in Latvia. The main thing is that most risks are predictable, but planning is necessary to reduce the probability of their occurrence.


Supporting Agencies
This research is funded by the Latvian Council of Science, project “Development of autonomous unmanned aerial vehicles based decision-making system for smart fruit growing”, project No. lzp2021/1-0134.


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How to Cite

L. Litavniece, S. Kodors, J. Dekšne, G. Lācis, I. Zarembo, and A. Pacejs, “RISK ANALYSIS FOR APPLE ORCHARD SURVEY AND MONITORING USING UAV”, ETR, vol. 1, pp. 116–122, Jun. 2023, doi: 10.17770/etr2023vol1.7234.