Process Optimization and Uncertainty Analysis of IoT-Integrated Cyclic Microwave-Assisted Extraction (CMAE) for...

Vanillin, the principal flavor compound in vanilla, is a high-value natural product whose conventional extraction is often limited by low efficiency and high energy consumption. Although microwave-assisted extraction (MAE) has improved extraction efficiency, most systems rely on continuous operation with limited real-time process monitoring. To address this limitation, an IoT-integrated cyclic microwave-assisted extraction (CMAE) system was developed for vanillin recovery from Vanilla planifolia. The system incorporated an infrared temperature sensor, a solid-state relay, an ESP32 microcontroller, and a Node-RED interface to enable real-time temperature monitoring and programmable cyclic microwave operation. Response surface methodology identified optimal conditions of 436 W microwave power, 16.93 min extraction time, 3.45 g sample mass on a dry-weight basis, and 75% ethanol, with a predicted vanillin content of 3.13% DW, equivalent to a yield of 31.29 mg/g DW. Monte Carlo simulation yielded a 95% uncertainty interval of 29.41-33.16 mg/g DW (2.94%-3.32% DW), whereas sensitivity analysis identified microwave power and ethanol concentration as the most influential variables. Experimental validation under approximately energy-equivalent conditions of 380 W for 19.44 min and 500 W for 14.78 min yielded 30.43 and 30.98 mg/g DW, respectively, with deviations from the predicted value below 3%. Assuming equivalent vanillin recovery, cyclic operation reduced the calculated nominal microwave energy input and specific energy consumption (SEC) by 16.7% relative to a calculated continuous-operation baseline. The developed CMAE system provides a data-driven extraction platform integrating IoT-based monitoring, programmable cyclic operation, process optimization, and uncertainty analysis, with potential application in energy-conscious phytochemical extraction.