DOI QR코드

DOI QR Code

A Study on IoT based Real-Time Plants Growth Monitoring for Smart Garden

  • Song, Mi-Hwa (Department of Information and Communication Science, Semyung University)
  • Received : 2020.01.18
  • Accepted : 2020.01.29
  • Published : 2020.02.29

Abstract

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

Keywords

References

  1. N. Sulaiman and M. Sadli, "An IoT-based Smart Garden with Weather Station System," in Proc. 9th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), pp. 38-43, 2019. DOI:10.1109/ISCAIE.2019.8743837
  2. M. Bacco, P. Barsocchi, E. Ferro, A. Gotta, and M. Ruggeri, "The Digitisation of Agriculture: a Survey of Research Activities on Smart Farming," Array, Vol. 3-4, September-December 2019. DOI: https://doi.org/10.1016/j.array.2019.100009
  3. D. Atia and H. El-madany, "Analysis and design of greenhouse temperature control using adaptive neuro-fuzzy inference system," Journal of Electrical Systems and Information Technology, Vol. 4, No. 1, pp.34-48, May 2017. DOI: https://doi.org/10.1016/j.jesit.2016.10.014
  4. H.S. Park, C.K. Park and, Y.S. Hong, "Smart Plants Management System based on Internet," The Journal of the Institute of Internet, Broadcasting and Communication(JIIBC), Vol. 15, No. 5, pp.193-199, October 2015. DOI: http://dx.doi.org/10.7236/JIIBC.2015.15.5.193
  5. A. Mateen, Q. Zhu, and S. Afsar, "IoT based real time agriculture farming," The International Journal of Advanced Smart Convergence, Vol. 8, No. 4, pp.16-25, 2019. DOI: http://dx.doi.org/10.7236/IJASC.2019.8.4.16
  6. R. Shamshiri, F. Kalantari, K. Ting, K. Thorp4, I. Hameed, C. Weltzien, D. Ahmad, and Z. Shad, "Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture," International Journal of Agricultural and Biological Engineering, Vol. 11, No. 1, pp. 1-22, January 2018. DOI: 10.25165/j.ijabe.20181101.3210
  7. Growtronix, http://Growtronix.com
  8. V. Balas, R. Kumar, and R. Srivastava, "Recent Trends and Advances in Artificial Intelligence and Internet of Things," Intelligent Systems Reference Library, Vol. 172, pp.507-520, 2020.
  9. PlantHive, http://www.planthive.com/
  10. Open-source hardware, https://en.wikipedia.org/wiki/Open-source_hardware
  11. NodeMCU, https://en.wikipedia.org/wiki/NodeMCU