Increasing Water Efficiency by Using Fuzzy Logic Control in Tomatoes Seedling Cultivation

Abstract

The biggest problem in agriculture is the insufficient amount of water. Sowing cannot be done in the fields due to water scarcity. Some fields become barren land due to excessive irrigation. For these reasons, it is important to use water wisely. In the study, irrigation of tomatoes seed is controlled with fuzzy logic. The use of water is made automatically according to the humidity, temperature and soil moisture of the air. The study was carried out in two stages. First stage; The irrigation system is designed in the MATLAB program. For this, temperature, humidity and soil moisture were used as three inputs. Irrigation time was calculated as output. All inputs and outputs are set to low, medium and high. In the second stage; equal amounts of tomatoes seeds were planted in two separate containers. Normal irrigation was done in the first pot. The control of irrigation in the second bowl was made with fuzzy logic. All data are shown on the screen and recorded for 1 minute. As a result of the study, 22500 milliliters of water were used in normal irrigation, and 10410 milliliters of water were used in a fuzzy logic-controlled circuit. As a result, a water saving of 53.77% was achieved. Arduino microcontroller is used for control. The code was written for the fuzzy logic control circuit simulated in the Arduino microcontroller MATLAB program to work. At the same time, temperature and humidity sensors are connected to the Arduino microcontroller. Incoming data is remotely monitored and controlled by a modem connected to the microcontroller. When the records in the database are examined, 83% energy was saved with lighting algorithm and energy flow control algorithms.

Keywords

• Fuzzy logic
• Productivity
• Tomato seedling
• Remote control

References

1. [1] Sudharshan N., Kasturi K., Sandeep K., Geetha S. Renewable Energy Based Smart Irrigation System. Procedia Computer Science 165 pp. 615–623, 2019
2. [2] Khandare S., Alone A., Patil S., Raut P. A Review on Solar Based Plant Irrigation System. International Research Journal of Engineering and Technology (IRJET) 5(2) pp. 1516-1518. 2018.
3. [3] Parameswaran G., & Sivaprasath K. Arduino based smart drip irrigation system using Internet of Things. International Journal of Engineering Science and Computing 6(5) pp. 5518-5521. 2016.
4. [4] Rehman A., Asif R., Tariq R., Javed A. GSM based solar automatic irrigation system using moisture, temperature and humidity sensors. International Conference on Engineering Technology and Technopreneurship (ICE2T) pp. 1-4. 2017.
5. [5] Venkatapur R. & Nikitha S. Review on Closed Loop Automated Irrigation System. The Asian Review of Civil Engineering 6(1): pp. 9-14. 2017.
6. [6] Zhang C., Li X. , Guo P., Huo Z. , Huang G. Enhancing irrigation water productivity and controlling salinity under uncertainty: a fuzzy dependent linear fractional programming approach. Journal of Hydrology. Vol:606 pp.127428-127439. 2022.
7. [7] Pacco H. C. Simulation of temperature control and irrigation time in the production of tulips using fuzzy logic. Procedia Computer Science. Vol:200 pp.1-12. 2022.
8. [8] Pazouki E. Practical surface irrigation design based on fuzzy logic and meta-heuristic algorithms. Agriculture Water Management Vol:256 pp:107659-107669.2022.

9. [9] Perea R. G., & Camacho E. Forecasting of applied irrigation depth at farm level for energy tariff periods using coactive neurogenetics fussy system. Agriculture Water Management Vol:256 pp:107068-107075. 2021.