Circular patch antenna as grain moisture sensor for smart agriculture

• Published in: Journal of Electrical Systems and Information Technology Vol. 12; no. 1; pp. 66 - 15
• Main Authors: Kaur, Preet, Bansal, Sonia, Manju
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2025; Springer Nature B.V; SpringerOpen
• Subjects: Agriculture; Antenna sensor; Antennas; Artificial Intelligence; Beans; Calibration; Cereals; Circular patch antenna; Dielectric properties; Electrical Engineering; Electrical Machines and Networks; Engineering; Ethernet; Grain; HFSS; Information Systems and Communication Service; Internet of Things; Lentils; Mechanical Engineering; Microstrip antenna; Moisture absorption; Moisture content; Moisture sensor; Network analysers; Patch antennas; Power Electronics; Real time; Regression coefficients; Rice; Sensitivity; Sensors; Thickness measurement; VNA; Antenna sensor; Circular patch antenna; Microstrip antenna; Moisture sensor; VNA; FR4; HFSS
• ISSN: 2314-7172; 2314-7172
• DOI: 10.1186/s43067-025-00261-6

This paper presents a low-cost circular patch antenna sensor developed for measurement of moisture content in lentils and rice. The proposed sensor was modeled and simulated in HFSS after that the prototype was fabricated by chemically etching the FR4 material of 1.6 mm thickness. Measurements were conducted using a Vector Network Analyzer. The presented antenna sensor is resonating at 2.45 GHz frequency. Calibration equations were obtained by utilizing moisture content and reflection coefficients values. The moisture content varied between 2.04 and 11.11% based on wet weight. A good agreement between the actual and calculated values of moisture content validates that this proposed antenna sensor could serve as a moisture sensor for rice and lentil grains. For rice, the sensitivity is found to be 0.0071, and the regression coefficient is equal to 0.9976. In case of lentil, the values of the regression coefficient and sensitivity are 0.9981 and 0.0088, respectively. Furthermore, a real-time moisture sensing setup has made using a laptop with LabVIEW software, ESP32 microcontroller, VNA, and an Ethernet connection. The moisture content values can be seamlessly displayed in real time on mobile devices or laptop for convenient monitoring and analysis.