Independently Operational Dual-Band Metamaterial based Smart EM Sensing System for Detection and Quantification of Adulteration in Cooking Oils

In this paper, a non-destructive smart electromagnetic( EM) sensing-system consisting of novel metamaterial-based resonator is proposed and demonstrated to detect and quantify various chemical adulterants in different popularly used cooking oils for X-band industrial and food-technology applications. It primarily involves a compact and advanced metamaterial based modified split-ring-resonator that shows dual-resonances with improved field confinement. Further, an anti-symmetric step structure is incorporated to achieve independent dual-frequency bands, necessary for detecting mineral oil, paraffin oil, pyridine and liquid-neon within coconut, mustard and olive oils explicitly in the permittivity range of 0.1-3. The best-suited optimization is carried out using the Genetic-Algorithm within the framework of the CST Microwave-Studio. A novel lab-made self-powered RF-transceiver module is further developed to independently generate the necessary input EM-signals for the sensing mechanism. Catering the smart detection for the larger population, a reverse-mapping algorithm is developed that compares the pre-loaded adulterated tested dataset and the sensed-data. Finally, by leveraging the frequency-shifting property and wirelessly transferring the sensed-data to visual-interface, the developed sensing-system accurately detects and quantifies the adulterants in cooking oils. The performance of the smart sensing-system is thoroughly examined through both theoretical analysis and experimental validation. The proposed smart sensing-system exhibits high sensitivity of 85%, Q-factor 212.5, FOM of 180, promising broad detection-range from 10%-100% while maintaining simplicity, compactness, robustness and user-friendly. The outcomes of the research surpass the achievements of previous studies on liquid-sensing holding promising applications in chemical, oil, microfluidic and food industries.