A liquid fertilizer concentration measurement system based on the microwave sensor and internet of things (IoT) technology

• Main Author: Lim, Zheng Yoong
• Format: Final Year Project / Dissertation / Thesis
• Published: 2022
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utar.edu.my/5387/1/MH_1800409_Final_%2D_ZHENG_YOONG.pdf; http://eprints.utar.edu.my/5387/
• Institution: Universiti Tunku Abdul Rahman

Many people are suffering from hunger, especially in the region of Africa. This shows that agricultural production is not enough to supply the food demand. Due to global warming, rising sea levels will reduce the land for agriculture and extreme weather event will occur more frequently. This will decrease the total crop yields and affect the global food supply. To overcome this problem, crop production must increase. By using a suitable concentration of liquid fertilizer on the crops, crop yields can rise significantly. Determination of the liquid fertilizer concentration accurately and fast is one of the ways to increase crop yields. All the system proposed by previous researchers does not integrate with Internet of Things (IoT) technology. The microwave sensor has the advantages of fast response time, non-intrusive and non-invasive which is suitable to use for liquid fertilizer concentration real time monitoring. This study proposed a planar microwave sensor to measure the urea and monoammonium phosphate (MAP) liquid fertilizer. The sensor characteristic is measured by a vector network analyser (VNA) to determine the frequencies that have a linear trend between the transmission coefficient (S21) and the concentration of liquid fertilizers. The sensitivity of urea is 3.20 dB/(g/mL) at 2.37 GHz and MAP is 1.13 dB/(g/mL) at 2.54 GHz. The liquid fertilizer concentration measurement system has been developed. The calibration equation is obtained by measuring the power detector output voltage. Next, the validation test is carried out by using the calibration equation. The validation result shows that the coefficient of determination (R2 ) is higher than 0.9 and the root mean square error (RMSE) is less than 0.1 for both fertilizers. IoT technology is integrated into this system. The measured concentration can be monitored using the developed android mobile application and web application while the data is stored in the Firebase Realtime Database.