IoT Enabled Non-Invasive Glucose Monitoring Through Breath Acetone

This paper presents a non-invasive blood glucose monitoring system integrated with Internet of Things (IoT) technology using breath acetone detection. The system utilizes a TGS822 gas sensor to detect acetone levels in exhaled breath, which are correlated with blood glucose concentration. To enhance accuracy, environmental parameters such as temperature, humidity, and pressure are measured using DHT11 and BMP180 sensors. Sensor data are processed using Arduino-based signal acquisition and regression analysis techniques to estimate glucose levels, which are displayed in real-time on an LCD and transmitted for remote monitoring. Experimental validation was conducted on 11 subjects, and results demonstrated a strong correlation with standard glucometer readings, achieving an accuracy of approximately 98%. The proposed system offers a reliable, painless, and cost-effective alternative for diabetes management.