DOI QR코드

DOI QR Code

Development of Cloud-based Smart Farm Management System while Considering Its Maintenance Aspects

  • Minseok Choi (Div. of A.I Convergence, Sahmyook University)
  • 투고 : 2024.09.30
  • 심사 : 2024.10.10
  • 발행 : 2024.11.30

초록

Measures to enhance a cloud-based smart farm management system were proposed to improve its efficiency and maintenance. The existing system had achieved efficiency and stability by utilizing a web-based operating program with a general-purpose microcomputer and Linux. However, this system faced issues with synchronization and maintenance while concurrent tasks were being performed. Synchronization issues were solved by implementing an embedded DB, and the system was upgraded to allow over-the-air (OTA) software updates. Additionally, a method was also proposed to enable remote maintenance using tunneling. It was determined that applying the proposed method can contribute to the widespread adoption of smart farms, in addition to reducing maintenance costs. Furthermore, this system can also be expanded into a universal system applicable to different service models in the future.

키워드

참고문헌

  1. H. S. Kim, D. D. Lee and H. S. Kim, "Strategies and Tasks of ICT Convergence for the Creative Agriculture Realization(R736)", Seoul: Korea Rural Economic Institute, 2014.
  2. Y. Lee and C. M. Heo, "A Study on the Influence of Acceptance Factors of ICT Convergence Technology on the Intention of Acceptance in Agriculture : Focusing on the Moderating Effect of Innovation Resistance", Journal of Digital Convergence, Vol. 17, No.9, pp. 115-126, 2019. DOI: https://doi.org/10.14400/JDC.2019.17.9.115
  3. M. H. Ahn and C. M Heo, "The Effect of Technical Characteristics of Smart Farm on Acceptance Intention by Mediating Effect of Effort Expectation", Journal of Digital Convergence, Vol. 17, No. 6, pp. 145-157, 2019. DOI: https://doi.org/10.14400/JDC.2019.17.6.145
  4. N. G. Yoon, J. S. Lee, G. S. Park and J. Y. Lee, "Korea smart farm policy and technology development status", Rural Resources, Vol. 59, No. 2, pp. 19-27, May 2017.
  5. Minseok Choi, "A study on the efficient Implementation method of cloud-based smart farm control system", Journal of Digital Convergence, Vol. 18, No. 3, pp. 171-177, 2019. DOI: https://doi.org/10.14400/JDC.2020.18.3.000
  6. S. Qazi, B. A. Khawaja and Q. U. Farooq, "IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends", IEEE Access, Vol. 10, pp. 21219-21235, 2022. DOI: https://doi.org/10.1109/ACCESS.2022.3152544
  7. Minseok Choi, "Smart Farm Management systemfor Improving Energy Efficiency", Journal of Digital Convergence, Vol. 19, No. 12, pp. 331-337, 2021. DOI: https://doi.org/10.14400/JDC.2021.19.12.331
  8. Widianto, M., Ardimansyah, M., Pohan, H. and Hermanus, D, "A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield", Journal of Robotics and Control(JRC), Vol. 3, No 3, pp. 269-278, May 2022. DOI: https://doi.org/10.18196/jrc.v3i3.13760
  9. Cambra Baseca, Carlos, Sandra Sendra, Jaime Lloret, and Jesus Tomas, "A Smart Decision System for Digital Farming", Agronomy Vol. 9, No. 5: 216, 2019. DOI: https://doi.org/10.3390/agronomy9050216
  10. H. Y. Shin, H. K. Yim and W. T. Kim, "Intelligent Green House Control System based on Deep Learning for Saving Electric Power Consumption", Journal of IKEEE, Vol. 22, No. 1, pp. 53-60, 2018. https://doi.org/10.7471/ikeee.2018.22.1.53
  11. Arshad, Jehangir, Musharraf Aziz, Asma A. Al-Huqail, Muhammad Hussnain uz Zaman, Muhammad Husnain, Ateeq Ur Rehman and Muhammad Shafiq, "Implementation of a LoRaWAN Based Smart Agriculture Decision Support System for Optimum Crop Yield", Sustainability, Vol.14, No. 2: 827, 2022. DOI: https://doi.org/10.3390/su14020827
  12. Li Chen and Jae Eun Yoon, "Research on Spatial Layout Characteristics of Intelligent Farm", Design Research, Vol. 9, No. 2, pp.457-471, 2024. DOI: https://doi.org/10.46248/kidrs.2024.2.457