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

Yıl 2022, , 165 - 176, 10.10.2022

Anıl Sezgin , Vesile Küçük

https://doi.org/10.53070/bbd.1172774

Öz

Tarım alanında yaşanan sorunların çözümünde akıllı teknolojilerin kullanımı önem kazanmaktadır. Çalışmaların önemli bir amacı da tarım ürünlerinin sera ortamlarında yetiştirilmesini sağlamaktır. Bu sayede akıllı sistemler tarafından kontrol edilen seralarda uygun toprak ve iklim koşulları oluşturularak tarım ürünlerinin yetiştirilmesi ve insanların bu ürünlere erişiminin kolaylaştırılması önemli bir araştırma ve uygulama konusu haline gelmiştir. Bu çalışmada, görüntü işleme teknikleri, makine öğrenmesi yöntemleri ve Nesnelerin İnterneti kullanılarak, bir ürünün yetiştirilmesinin takip edilmesi ve uygun yetiştirme koşullarının belirlenmesi amaçlanmaktadır.

Anahtar Kelimeler

Görüntü İşleme, Makine Öğrenmesi, Nesnelerin İnterneti, Sensörler

Destekleyen Kurum

İstanbul Esenyurt Üniversitesi

Proje Numarası

BAP 2020/02

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

Image Processing, Machine Learning, Internet of Things, Sensors

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.
• Gan, W., Zhu, Y., and Zhang, T. (2010), “On RFID application in the tracking and tracing system of agricultural product logistics,” in International Conference on Computer and Computing Technologies in Agriculture. Nanchang, China: Springer, pp. 400–407.
• García-Lesta, D., Cabello, D., Ferro, E., López, P., and Brea, V.M. (2017), “Wireless sensor network with perpetual motes for terrestrial snail activity monitoring,” IEEE Sensors J., vol. 17, no. 15, pp. 5008–5015.
• Giri, A., Dutta, S. and Neogy, S. (2016), “Enabling agricultural automation to optimize utilization of water, fertilizer and insecticides by implementing Internet of Things (IoT),” in Proc. Int. Conf. Inf. Technol. (InCITe) Next Gener. IT Summit Theme Internet Things Connect Your Worlds, pp. 125–131.
• Gómez-melendez, D., López-lambraño, A., Ruiz, G.H., Rico-garcia, E., Olvera-olvera, C., and Alaniz-lumbrerasc, D. (2011), “Fuzzy irrigation greenhouse control system based on a field programmable gate array”, African J. Agric. Res., vol. 6, no. 11, pp. 2544–2557.
• Gosavi, J.V. (2017), “Water monitoring system for hydroponics agriculture”, International Journal for Research in Applied Science and Engineering Technology, vol. 5, no. 7, pp 234-238.
• Huang, L., and Liu, P. (2014), Key Technologies and Alogrithms’ Application in Agricultural Food Supply Chain Tracking System in E-Commerce. Beijing, China: Springer, pp. 269–281, doi: 10.1007/978-3-642-54341-8-29.
• Kaloxylos, A., Eigenmann, R., Teye, F., Politopoulou, Z., Wolfert, S., Shrank, C., Dillinger, M., Lampropoulou, I., Antoniou, E., Pesonen, L., Nicole, H., Thomas, F., Alonistioti, N., Kormentzas, G. (2012), “Farm management systems and the future Internet era,” Comput. Electron. Agricult., vol. 89, pp. 130–144.
• Kodali, R.K., Jain, V., and Karagwal, S. (2016), “IoT based smart greenhouse,” in Proc. IEEE Region 10 Humanitarian Technol. Conf. (R10-HTC), pp. 1–6.
• Lee, H., Moon, A., Moon, K., and Lee, Y. (2017), “Disease and pest prediction IoT system in orchard: A preliminary study,” in Proc. 9th Int. Conf. Ubiquitous Future Netw. (ICUFN), Milan, Italy, pp. 525–527.
• Lerdsuwan, P., and Phunchongharn, P. (2017), “An energy-efficient transmission framework for IoT monitoring systems in precision agriculture,” in International Conference on Information Science and Applications. Singapore: Springer, pp. 714–721.
• Li, L. (2011), “Application of the Internet of Thing in green agricultural products supply chain management,” in Proc. IEEE Int. Conf. Intell. Comput. Technol. Autom. (ICICTA), vol. 1. Shenzhen, China, pp. 1022–1025.
• Ludwig, F., Fernandes, D.M., Mota, P., Bôas, R. (2013), Electrical conductivity and pH of the substrate solution in gerbera cultivars under fertigation. Hortic. Bras. 31 (3), 356–360.
• Manrique, J.A., Rueda-Rueda, J.S., and Portocarrero, J.M.T. (2016), “Contrasting Internet of Things and wireless sensor network from a conceptual overview,” in Proc. IEEE Int. Conf. Internet Things (iThings) IEEE Green Comput. Commun. (GreenCom) IEEE Cyber Phys. Soc. Comput. (CPSCom) IEEE Smart Data (SmartData), Chengdu, China, pp. 252–257.
• Mainetti, L., Mele, F., Patrono, L., Simone, F., Stefanizzi, M.L., Vergallo, R. (2013), “An RFID-based tracing and tracking system for the fresh vegetables supply chain,” Int. J. Antennas Propag., vol. 2013, Art. no. 531364.
• Mat, I., Kassim, M.R.M., Harun, A.N., and Yusoff, I.M. (2016), “IoT in precision agriculture applications using wireless moisture sensor network,” in Proc. IEEE Conf. Open Syst. (ICOS), pp. 24–29.
• Morimoto, T., and Hashimoto, Y. (1991), “Application of fuzzy logic and neural network to the process control of solution pH in deep hydroponic culture,” IFAC Proc. Vol., vol. 24, no. 11, pp. 147–152.
• Munandar, A., Fakhrurroja, H., Rizqyawan, M. I., and Pratama, R.P. (2017), “Design of Real-time Weather Monitoring System Based on Mobile Application using Automatic Weather Station”, International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT), pp. 44–47.
• Oksanen, T., Linkolehto, R., and Seilonen, I. (2016), “Adapting an industrial automation protocol to remote monitoring of mobile agricultural machinery: A combine harvester with IoT,” IFAC PapersOnLine, vol. 49, no. 16, pp. 127–131.
• Pekoslawski, B., Krasinski, P., Siedlecki, M., and Napieralski, A. (2013), “Autonomous wireless sensor network for greenhouse environmental conditions monitoring,” in Proc. 20th Int. Conf. Mixed Design Integr. Circuits Syst. (MIXDES), pp. 503–507.
• Peuchpanngarm, C., Srinitiworawong, P., Samerjai, W., Sunetnanta, T. (2016), DIY sensorbased automatic control mobile application for hydroponics. In: Proc. 2016 5th ICT Int. Student Proj. Conf. ICT-ISPC, pp. 57–60.
• Pitakphongmetha, J., Boonnam, N., Wongkoon, S., Horanont, T., Somkiadcharoen, D., Prapakornpilai, J. (2016), Internet of things for planting in smart farm hydroponics style. In: 20th Int. Comput. Sci. Eng. Conf. Smart Ubiquitous Comput. Knowledge, ICSEC.
• Regattieri, A., Gamberi, M., and Manzini, R. (2007), “Traceability of food products: General framework and experimental evidence,” J. Food Eng., vol. 81, no. 2, pp. 347–356.
• Rubala, J.I., and Anitha, D. (2017), “Agriculture field monitoring using wireless sensor networks to improving crop production,” Int. J. Eng. Sci., vol. 5216, pp. 5216–5221.
• Suhardiyanto, H., Seminar, K.B., Chadirin, Y., and Setiawan, B.I. (2011), “Development Of A pH Control System For Nutrient Solution In EBB And Flow Hydroponic Culture Based On Fuzzy Logic,” IFAC Proc. Vol., vol. 34, no. 11, pp. 87–90.
• Tripicchio, P., Satler, M., Dabisias, G., Ruffaldi, E., and Avizzano, C.A. (2015), “Towards smart farming and sustainable agriculture with drones,” in Proc. IEEE Int. Conf. Intell. Environ. (IE), Prague, Czech Republic, pp. 140–143.
• Wang, N., Zhang, N., and Wang, M. (2006), “Wireless sensors in agriculture and food industry—Recent development and future perspective,” Comput. Electron. Agricult., vol. 50, no. 1, pp. 1–14.
• Zhang, P., Zhang, Q., Liu, F., Li, J., Cao, N., and Song, C. (2017), “The construction of the integration of water and fertilizer smart water saving irrigation system based on big data” in Proc. IEEE Int. Conf. Comput. Sci. Eng. (CSE) IEEE Int. Conf. Embedded Ubiquitous Comput. (EUC), vol. 2. Guangzhou, China, pp. 392–397.
• Zhang, S., Chen, X., and Wang, S. (2014), “Research on the monitoring system of wheat diseases, pests and weeds based on IoT,” in Proc. 9th Int. Conf. Comput. Sci. Educ., Vancouver, BC, Canada, pp. 981–985.
• Zhao J.C., Zhang, J.F., Feng, Y., and Guo, J.X. (2010), “The study and application of the IoT technology in agriculture,” in Proc. 3rd Int. Conf. Comput. Sci. Inf. Technol., vol. 2. Chengdu, China, pp. 462–465.