IoT-Enabled SnO₂-Based Humidity Sensor for Real-Time Monitoring in Neonatal Incubators.

This research presents the development and optimization of a Tin Oxide (SnO₂)-based resistive humidity sensor for accurate monitoring in incubator systems. SnO₂ nanomaterials were synthesized using hydrothermal synthesis technique, followed by comprehensive characterization through X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), current-voltage (J-V) analysis, ultravioletvisible (UV-Vis) spectroscopy, and electrochemical impedance spectroscopy (EIS). The best-performing sensor exhibited a flower-like nanostructure with a response time of 18 s, a recovery time of 14 s, and a sensitivity of 72.4%. The sensor functioned effectively within the required incubator humidity range of 40-60% relative humidity (RH) and demonstrated superior performance compared to the commercial DHT11 sensor. To ensure accuracy and reliability, machine learning algorithms were applied to estimate error and validate the correctness of the sensed humidity data. The optimized SnO₂ sensor was integrated into an incubator system, with real-time data transmission enabled through an Internet of Things (IoT) platform. These findings highlight the potential of SnO₂-based sensors for high-precision humidity monitoring in biomedical applications, particularly for neonatal care where stable humidity levels are critical.