Faculty of Electrical and Electronic Engineering and AutomationBook 3.1 · Electrical Engineering, Electronics and Automation

FRI-10.326-1-EEEA-08

APPLICATION OF IOT-BASED SOIL SENSORS AND FUZZY LOGIC TO CONTROL A DRIP IRRIGATION SYSTEM

Reni Kabakchieva

Department of Electronics University of Ruse “Angel Kanchev” Ruse, Bulgaria

E-mail: rkabakchieva@uni-ruse.bg

Prof. Boris Evstatiev

Department of Electronics University of Ruse “Angel Kanchev” Ruse, Bulgaria

ORCID: 0000-0003-1508-9629

E-mail: bevstatiev@uni-ruse.bg

Abstract

Modern agriculture is unthinkable without the application of new knowledge-intensive and effective technologies for optimization and increase of yields while simultaneously complying with environmental norms. Drip irrigation has the advantages mentioned in this paper and is therefore widely used. The electronic IoT based drip irrigation system presented in this paper aims at process automation and optimization. It was developed at the University of Ruse "Angel Kanchev" and its operability was experimentally verified. The results are shown graphically and the methodology by which the experiments were carried out is described.

Keywords

IoT, Fuzzy Logic, PV-powered, electronic system, LoRa

REFERENCES

Ho, A. M., Jaafar, H. Z., Grozescu, I. V., & Zaharin, M. Z. A. B. (2015). Solar Powered Gravity-Feed Drip Irrigation System Using Wireless Sensor Network. International Journal of Environmental Science and Development, 6(12), 970.
Huntley J. (2014) Design and evalutation of a drip irrigation system on Apple orchard in Julian, CA, BioResource and Agricultural Engineering Department California Polytechnic State University San Luis Obispo
Liao Z., S. Dai, and C. Shen, (2012) Precision agriculture monitoring system based on wireless sensor networks, Proc. ICWCA International Conf. on Wireless Communications and Applications, pp. 1-5.
Li, M., Sui, R., Meng, Y., & Yan, H. (2019). A real-time fuzzy decision support system for alfalfa irrigation. Computers and Electronics in Agriculture, 163, 104870.
MARTÍNEZ J., RECA J. (2014) Water use efficiency of surface drip irrigation versus an alternative subsurface drip irrigation method. Journal of Irrigation and Drainage Engineering. Vol. 745. Iss. 1 p. 733-743.
Mohammed, B., Bekkay, H., Migan-Dubois, A., Adel, M., & Rabhi, A. (2021). An intelligent irrigation system based on fuzzy logic control: A case study for Moroccan oriental climate region. In 2nd international conference on Embedded Systems and Artificial Intelligence (ESAI’21).
Rewatkar R. R., S. B., Hedau, S. R., Mudliyar, M. A., Dharmik, and P. A., Bhede, (2016) Automation in drip irrigation using embedded control system. International Journal of Science, Engineering and Technology Research (IJSETR). 5(4), 860-863
Fernández-Ahumada, L. M., Ramírez-Faz, J., Torres-Romero, M., & López-Luque, R. (2019). Proposal for the design of monitoring and operating irrigation networks based on IoT, cloud computing and free hardware technologies. Sensors, 19(10), 2318.
Roopaei, M., Rad, P., Choo, K.R., Choo, R., (2017) Cloud of things in smart agriculture: intelligent irrigation monitoring by thermal imaging. IEEE Cloud Comput. 4, 10-15.
Rathore, P. K. S., Das, S. S., & Chauhan, D. S. (2018). Perspectives of solar photovoltaic water pumping for irrigation in India. Energy strategy reviews, 22, 385-395.
Таneva A., I. Ganchev M. Petrov. (2019) Fuzzy logic in control, TU Sofia, Plovdiv branch, Faculty of Electronics and Automation, Control Systems Department, 25 Tsanko Dyustabanov Str.,4000 Plovdiv, Bulgariа
Tenev, B. (2012) OPERATING MANUAL FOR DRIP IRRIGATION SYSTEM FOR APPLE PLANTATION. Water and Rural Institute - Sofia, http://www.thewri.eu/documents/techs/1.pdf (Оригинално заглавие: Бойчо Тенев, инж-ик. РЪКОВОДСТВО ЗА ЕКСПЛОАТАЦИЯ НА СИСТЕМА ЗА КАПКОВО НАПОЯВАНЕ НА ЯБЪЛКОВО НАСАЖДЕНИЕ. Институт по водите и селските райони - София)