Research Article

Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System

Volume: IDAP-2022 : International Artificial Intelligence and Data Processing Symposium October 10, 2022
EN TR

Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System

Abstract

The use of smart technologies is gaining importance in solving the problems experienced in the field of agriculture. An important aim of the studies is to ensure the cultivation of agricultural products in greenhouse environments. In this way, growing agricultural products in greenhouses controlled by smart systems by creating suitable soil and climatic conditions and facilitating people’s access to these products has become an important research and application topic. This study aims to follow the cultivation of a product and determine suitable growing conditions by using image processing techniques, machine learning methods, and the Internet of Things.

Keywords

Supporting Institution

İstanbul Esenyurt Üniversitesi

Project Number

BAP 2020/02

References

  1. Abhishesh, P., Ryuh, B., Oh, Y., Moon, H., and Akanksha, R. (2017), “Multipurpose agricultural robot platform: Conceptual design of control system software for autonomous driving and agricultural operations using programmable logic controller,” World Acad. Sci. Eng. Technol. Int. J. Mech. Aerosp. Ind. Mechatronic Manuf. Eng., vol. 11, no. 3, pp. 496–500.
  2. Abu, M.A., and Yacob, M.Y. (2013), "Development and simulation of an agriculture control system using fuzzy logic method and visual basic environment", In 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems, pp. 135-142.
  3. Amin, M.S.M., Aimrun, W., Eltaib, S.M., and Chan, C.S. (2004), “Spatial soil variability mapping using electrical conductivity sensor for precision farming of rice,” Int. J. Eng. Technol., vol. 1, no. 1, pp. 47–57.
  4. Benaissa, S., Plets, D., Tanghe, E., Trogh, J., Martens, L., Vandaele, L., Verloock, L., Tuyttens, F.A.M., Sonck, B., Joseph, W. (2017), “Internet of animals: Characterisation of LoRa subGHz off-body wireless channel in dairy barns,” Electron. Lett., vol. 53, no. 18, pp. 1281–1283.
  5. Dan, L., Xin, C., Chongwei, H., and Liangliang, J. (2015), “Intelligent agriculture greenhouse environment monitoring system based on IoT technology,” in Proc. Int. Conf. Intell. Transport. Big Data Smart City, pp. 487–490.
  6. Dlodlo, N., and Kalezhi, J. (2015), “The Internet of Things in agriculture for sustainable rural development,” in Proc. Int. Conf. Emerg. Trends Netw. Comput. Commun. (ETNCC), pp. 13–18.
  7. Ferentinos, K.P., Albright, L.D. (2007), Predictive neural network modeling of Ph and electrical conductivity in deep-trough hydroponics. Trans. ASAE 45 (6), 2007–2015.
  8. Fuangthong, M., and Pramokchon, P. (2018), “Automatic control of electrical conductivity and PH using fuzzy logic for hydroponics system,” in 2018 International Conference on Digital Arts, Media and Technology (ICDAMT), pp. 65–70.

Details

Primary Language

English

Subjects

Artificial Intelligence, Software Engineering, Control Engineering, Mechatronics and Robotics

Journal Section

Research Article

Publication Date

October 10, 2022

Submission Date

September 8, 2022

Acceptance Date

September 21, 2022

Published in Issue

Year 2022 Volume: IDAP-2022 : International Artificial Intelligence and Data Processing Symposium

APA
Sezgin, A., & Küçük, V. (2022). Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System. Computer Science, IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, 165-176. https://doi.org/10.53070/bbd.1172774
AMA
1.Sezgin A, Küçük V. Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System. JCS. 2022;IDAP-2022 : International Artificial Intelligence and Data Processing Symposium:165-176. doi:10.53070/bbd.1172774
Chicago
Sezgin, Anıl, and Vesile Küçük. 2022. “Monitoring Plant Growth With Image Processing Methods and Artificial Intelligence Supported Agriculture System”. Computer Science IDAP-2022 : International Artificial Intelligence and Data Processing Symposium (October): 165-76. https://doi.org/10.53070/bbd.1172774.
EndNote
Sezgin A, Küçük V (October 1, 2022) Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System. Computer Science IDAP-2022 : International Artificial Intelligence and Data Processing Symposium 165–176.
IEEE
[1]A. Sezgin and V. Küçük, “Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System”, JCS, vol. IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, pp. 165–176, Oct. 2022, doi: 10.53070/bbd.1172774.
ISNAD
Sezgin, Anıl - Küçük, Vesile. “Monitoring Plant Growth With Image Processing Methods and Artificial Intelligence Supported Agriculture System”. Computer Science IDAP-2022 : INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (October 1, 2022): 165-176. https://doi.org/10.53070/bbd.1172774.
JAMA
1.Sezgin A, Küçük V. Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System. JCS. 2022;IDAP-2022 : International Artificial Intelligence and Data Processing Symposium:165–176.
MLA
Sezgin, Anıl, and Vesile Küçük. “Monitoring Plant Growth With Image Processing Methods and Artificial Intelligence Supported Agriculture System”. Computer Science, vol. IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, Oct. 2022, pp. 165-76, doi:10.53070/bbd.1172774.
Vancouver
1.Anıl Sezgin, Vesile Küçük. Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System. JCS. 2022 Oct. 1;IDAP-2022 : International Artificial Intelligence and Data Processing Symposium:165-76. doi:10.53070/bbd.1172774

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