Development of Spray Calculation Algorithm Using the Pest Control Drones

농업용 방제드론의 방제면적 산출 알고리즘에 관한 연구

  • Lim, Jin-Taek (Department of Electricity, VISION College of Jeonju)
  • 임진택 (전주비전대학교 전기과)
  • Received : 2020.09.14
  • Accepted : 2020.10.20
  • Published : 2020.10.28


In the recent farming industry, there is a growing diffusion of drones, which are recognized as a crucial technology of the 4 th industrial revolution to cope with aging. Especially, filming and pest control using drones are representative fields that have different age groups for obtaining a national license of multicopter that is a ultra-light flying device, and can create profits after getting a license. However, pest control technology using drones has different spray effects depending on levels of operational proficiency, since this highly relies on an operator's operating skills. It is anticipated that if this issue is supplemented, the use of drones for pest control in the farming industry will diversify. For analysis of spraying characteristics of agricultural pest control drones, this study aims to formulate effective spraying hours and effective spraying intervals and suggest an algorithm, which facilitates an accurate calculation of pest control area depending on the kinds of pest control drones. This algorithm can be used in the field of pest control by improving scatterling issues caused by drone flight methods of drone pest controllers and building an optimum pest control manual in future.

최근 농업분야에서는 드론의 보급으로 인하여 노령화를 해결하기 위한 4차 산업 혁명의 중요 기술로 분류되고 있다. 특히, 초경량비행장치 멀티콥터의 국가 자격증을 취득하고자하는 연령대가 다양하고 취득 후 수익 활동을 위한 분야로는 드론을 활용한 영상 촬영 및 방제가 대표적이다. 그러나 드론을 활용한 방제기술은 조종자의 조종 기술의 의존도가 높아 조종 숙련에 따라 살포효과의 차이가 발생한다. 이를 보완한다면 농업의 방제분야의 활용도가 다양해 질 것으로 기대된다. 대표적인 보완 기술은 농업용 방제드론의 기체 특성을 고려한 정확한 방제면적이 산출이다. 본 논문에서는 농업용 방제드론의 살포 특성 분석을 위하여 유효살포시간, 유효살포간격을 정식화하고 방제드론 종류에 따른 정확한 방제면적 산출이 가능한 알고리즘을 제안한다. 추후 본 알고리즘을 기반으로 드론방제사의 비행 방식에 따른 비산 문제를 개선하고 최적의 방제 매뉴얼을 구축하여 방제 현장에 활용하고자 한다.



This research was supported by funds of Vision College of Jeonju


  1. J. D. Lee & C. M. Heo. (2020). The Effect of Technology Acceptance Factors on Behavioral Intention for Agricultural Drone Service by Mediating Effect of Perceived Benefits. Journal of Digital Convergence. 18(8), 151-167. DOI : 10.14400/JDC.2020.18.8.151
  2. Y. S. Ha. (2019). A Study on the System Configuration and Communication Equipment Operation for Mission and Control of Small UAV. Journal of Convergence for Information Technology, 9(11), 118-124. DOI : 10.22156/CS4SMB.2019.9.11.118
  3. C. Y. Ju. (2018). Design of Supervisors for the Control of Agricultural Multiple UAV Systems: A Preliminary Result. Journal of Institute of Control, Robotics and Systems, 24(11), 1005-1013. DOI : 10.5302/J.ICROS.2018.18.0161
  4. H. W. Chung, Y. G. Ha, M. H. Im, J. E. Shin, J. A. Do, J. H. Cho, K. S. Kwon & S. H. Park. (2011). Establishment of 22 Pesticide MRLs in Agricultural Products based on Risk Assessment. Korean J Environ Agric, 30(2), 156-162. DOI : 10.5338/KJEA.2011.30.2.156
  5. H. Y. Kim, S. H. Yoon, H. J. Park, J. H. Lee, I. S. Gwak, H. S. Moon, M. H. Song, Y. M. Jang, M. S. Lee, J. S. Park & K. H. Lee. (2007). Monitoring of Residual Pesticides in Commercial Agricultural Products in Korea. Korean J. Food Sci. Technol, 39(3), 237-245. DOI : 10.35272/jaet.2019.12.2.77
  6. J. H. Kim, S. J. Nam & J. Y. Song. (2020). Susceptibility of Pine Wood Nematode Vectors to ULV Insecticides Sprayed from an Unmanned Helicopter. Korean Journal of Applied Entomology. 59(2), 83-91. DOI : 10.5656/KSAE.2020.03.0.005
  7. Y. D. Jin, H. D. Lee, Y. K. Park, J. B. Kim & O. K. Kwon. (2008). Drift And Distribution Properties Of Pesticide Spray Solution Applied Aerially By Manned-Helicopter. The Korean Journal Of Pesticide Science. 12(4), 351-356.
  8. S. K. Kim, D. Y. Lim & S. Y. Jung, J. (2019). Low Cost Evaluation Method of Agricultural Drone with Simulated Spraying System. J. of Advanced Engineering and Technology, 12(2), 77-84. DOI : 10.35272/jaet.2019.12.2.77
  9. J. T. Lim. (2019). A Study on the Characteristic Analysis of the Pest Control Drones Using Smart Operating Mode. Journal of Convergence for Information Technology, 9(10), 108-113. DOI : 10.22156/CS4SMB.2019.9.10.108
  10. I. Y. Hong & B. A. Chun. (2020). Participatory Mapping Using Low-cost Drone and Open Source Software. Journal of the Korean Cartographic Association, 20(1), 25-36. DOI: 10.16879/jkca.2020.20.1.025
  11. S. J. Oh. (2019). Database Design for Management of Forest Resources using a Drone. The Journal of the Convergence on Culture Technology, 5(3), 251-256. DOI : 10.17703/JCCT.2019.5.3.251
  12. S. H. Yu, Y. K. Kim, I. S. Choi, J. K. Woo, C. S. Hyun, T. G. Kang, H. J. Jun, S. H. Lee, J. G. Kim & Y. Choi. (2019, October). Analysis of Utilization Status and Spray Nozzle Characteristics and of Agricultural Drones. The Korean Society of the Agricultureal machinery, 40(6), 96.
  13. Y. M. Koo & Y. H. Bae. (2018). Uniformity Analysis of Unmanned Aerial Application with Variable Rate Spray System, Journal of Agriculture & Life Science, 52(6), 111-125.