AI-Enhanced 2.45 GHz Microstrip Patch Sensor for Milk Adulteration Detection

This paper introduces the design, development and testing of a 2.45 GHz microstrip circular patch antenna for detecting adulteration content in milk. The simulation and free-space test results of the antenna were presented. The proposed antenna was simulated using HFSS and optimized using AI models such as Linear Regression, SVR, and Random Forest Regression to enhance sensitivity and efficiency. The free-space results of the fabricated antenna demonstrated a resonant frequency of approximately 2.34 GHz and S21 of -27.08 dB closely aligning with the designed specifications. Extensive free-space testing demonstrated the antenna's reliability and efficiency, achieving consistent performance metrics with minimal reflection loss and optimized sensitivity.