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Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System
Öz
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.
Anahtar Kelimeler
Destekleyen Kurum
İstanbul Esenyurt Üniversitesi
Proje Numarası
BAP 2020/02
Kaynakça
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Yapay Zeka, Yazılım Mühendisliği, Kontrol Mühendisliği, Mekatronik ve Robotik
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
10 Ekim 2022
Gönderilme Tarihi
8 Eylül 2022
Kabul Tarihi
21 Eylül 2022
Yayımlandığı Sayı
Yıl 2022 Cilt: 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, ve 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 (Ekim): 165-76. https://doi.org/10.53070/bbd.1172774.
EndNote
Sezgin A, Küçük V (01 Ekim 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 ve V. Küçük, “Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System”, JCS, c. IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, ss. 165–176, Eki. 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 (01 Ekim 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, ve Vesile Küçük. “Monitoring Plant Growth with Image Processing Methods and Artificial Intelligence Supported Agriculture System”. Computer Science, c. IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, Ekim 2022, ss. 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. 01 Ekim 2022;IDAP-2022 : International Artificial Intelligence and Data Processing Symposium:165-76. doi:10.53070/bbd.1172774
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