미래기술융합논문지 (Journal of Advanced Technology Convergence)

한국융합학회 (Korea Convergence Society)
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시설 재배 농가 관리를 위한 데이터 서비스 기반의 비상 알림 스마트팜 서비스 모델 설계

Design of Emergency Notification Smart Farm Service Model based on Data Service for Facility Cultivation Farms Management

  • 방찬우 (서원대학교 정보통신공학과) ;
  • 이병권 (서원대학교 멀티미디어학과)
  • 투고 : 2022.09.01
  • 심사 : 2022.09.23
  • 발행 : 2022.09.30
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초록

2015년부터 정부에서는 한국형 스마트팜 보급에 노력하고 있다. 그러나, 기술 및 현행 재배 연구 데이터의 한계로 인해 대규모 시설 채소 농가에만 보급이 국한되고 있는 실정이다. 또한, 작물 생육 및 재배 환경을 고려하지 않은 IT 기술의 단순 적용으로 도입 비용 대비 효율성과 신뢰성이 낮은 상황이다. 따라서, 본 논문에서는 공공 및 외부 데이터를 기반으로 데이터 분석 서비스를 수행하고 이를 시설 재배 농가의 실정에 맞는 데이터 기반의 타깃형 스마트팜 시스템을 설계하였다. 이를 위해, 농장 위험 정보 알림 서비스를 개발하고, 적정 비료 시비를 위한 광환경지도를 제공하며, 시설 농장의 온습도 정보를 활용한 재배 작기별 병해 예측 모델을 설계하였다. 이를 통해, 기존의 스마트팜 센서 데이터와의 연계, 활용으로 스마트팜 데이터 서비스 구현이 가능하며, 데이터 활용에 경제적 효율성 및 데이터 신뢰성을 확보할 수 있다.

Since 2015, the government has been making efforts to distribute Korean smart farms. However, the supply is limited to large-scale facility vegetable farms due to the limitations of technology and current cultivation research data. In addition, the efficiency and reliability compared to the introduction cost are low due to the simple application of IT technology that does not consider the crop growth and cultivation environment. Therefore, in this paper, data analysis services was performed based on public and external data. To this end, a data-based target smart farm system was designed that is suitable for the situation of farms growing in facilities. To this end, a farm risk information notification service was developed. In addition, light environment maps were provided for proper fertilization. Finally, a disease prediction model for each cultivation crop was designed using temperature and humidity information of facility farms. Through this, it was possible to implement a smart farm data service by linking and utilizing existing smart farm sensor data. In addition, economic efficiency and data reliability can be secured for data utilization.

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참고문헌

  1. M. S. Choi. (2021). Smart Farm Control System for Improving Energy Efficiency. Journal of Digital Convergence, 19(12), 331-337. DOI : 10.14400/JDC.2021.19.12.331
  2. N. M. Hashem & A. Gonzalez-Bulnes. (2020). State-of-the-Art and Prospective of Nanotechnologies for Smart Reproductive Management of Farm Animals. Animals, 10(5), 840. DOI : 10.3390/ani10050840
  3. D. P. Kim, J. Y. Choi & S. Y. Choi. (2017). The Impacts of Personal Characteristics and Recognition of External Environments for the Prospective Smart Farm Agricultural Entrepreneurs on the Entrepreneurial Intention of Smart Farm Startups: Foc. Institute for Poverty Alleviation and International Development, 26(3), 183-218. DOI : 10.18350/ipaid.2017.26.3.183
  4. H. R. Hur, S. G. Park & M. C. Park. (2019). Design of Smart Farm with Automatic Transportation Function. Journal of the Korea Society of Computer and Information, 24(8), 37-43. DOI : 10.9708/jksci.2019.24.08.037
  5. Y. C. Choi & I. H. Jang. (2019). Smart Farm in the Age of the Fourth Industrial Revolution. The Journal of The Korean Institute of Communication Sciences, 36(3), 9-16.
  6. I. H. Jang, S. H. Yang, D. Y. Lee & D. W. Choi. (2018). Development of Agricultural Work Management System Based on Real-time Acquisition of Labor using Unmanned Transfer Robots. Journal of Institute of Control, Robotics and Systems, 24(11), 1014-1019. DOI : 10.5302/J.ICROS.2018.18.0167
  7. P. Choudhari, A. Borse & H. Chauhan. (2018). Smart Irrigation and Remote Farm Monitoring System. International Journal of Computer Applications, 180(38), 24-26. DOI : 10.5120/ijca2018917011
  8. H. Gan & W. S. Lee. (2018). Development of a Navigation System for a Smart Farm. IFAC-PapersOnLine, 51(17), 1-4. DOI : 10.1016/j.ifacol.2018.08.051
  9. I. Ullah & D. H. Kim. (2018). An Optimization Scheme for Water Pump Control in Smart Fish Farm with Efficient Energy Consumption. Processes, 6(6), 65. DOI : 10.3390/pr6060065
  10. S. Zhong & X. Wang. (2018). Decentralized Model-Free Wind Farm Control via Discrete Adaptive Filtering Methods. IEEE Transactions on Smart Grid, 9(4), 2529-2540. DOI : 10.1109/tsg.2016.2614434
  11. S. H. Kim. (2021). A Study on the Smart Farm Policy Process : Focusing on the Rogers' Innovation Process Model This study amended and supplemented some of the doctoral dissertations. Cooperative Economics and Management Review, 54, 87-116. DOI : 10.35443/CMR.2021.54..005
  12. B. H. Shin & H. K. Jeon. (2020). ICT-based Smart Farm Design. Journal of Convergence for Information Technology, 10(2), 15-20. DOI : 10.22156/CS4SMB.2020.10.02.015
  13. M. J. O'Grady & G. M. P. O'Hare. (2017). Modelling the smart farm. Information Processing in Agriculture, 4(3), 179-187. DOI : 10.1016/j.inpa.2017.05.001
  14. Y. J. Lee & Y. H. Pan. (2021). A Study on the Interaction Structure of Smart Farm in Controlled Horticulture: Focusing on Plant Production Stage. Journal of the Korea Convergence Society, 12(6), 1-8. DOI : 10.15207/JKCS.2021.12.6.001
  15. R. Mythili, M. Kumari, A. Tripathi & N. Pal. (2019). IoT Based Smart Farm Monitoring System. International Journal of Recent Technology and Engineering, 8(4), 5490-5494. DOI : 10.35940/ijrte.D8806.118419
  16. Y. T. Ju, S. C. Kim & E. K. Kim. (2021). Development of a Low Cost Smart Farm System for Cultivating High Value-added Specialized Crops. The Journal of the Korea institute of electronic communication sciences, 16(4), 743-748. DOI : 10.13067/JKIECS.2021.16.4.743