An IOT, ML and Breath Based Non Invasive Glucose Meter

The project introduces a non-invasive glucometer designed to revolutionize diabetes management through breath analysis. It focuses on identifying and analyzing volatile organic compounds (VOCs) in human breath that correlate with blood glucose levels. The process includes thorough chemical investigation to isolate and validate these VOCs as reliable biomarkers of glucose concentration. Advanced sensor design and calibration are crucial, utilizing cutting-edge materials and technology to create highly sensitive and accurate sensors for VOC detection. Beyond sensor development, the project leverages complex algorithms and machine learning techniques to establish precise correlations between VOC levels and blood glucose levels. A prototype will be created and tested with clinical samples to ensure that the device meets medical and regulatory standards. This multidisciplinary project combines chemistry, electronics, software engineering, and healthcare to deliver a seamless and user-friendly alternative to traditional blood glucose monitoring, eliminating the need for finger pricking. The aim is to improve patient comfort and compliance, leading to better diabetes management and enhanced quality of life for individuals with the condition.

Keywords: Non-invasive glucometer, diabetes management, breath analysis, volatile organic compounds (VOCs), biomarkers, sensor design, machine learning, prototype development, clinical testing, glucose monitoring, multidisciplinary approach, patient comfort, quality of life.

 Non-invasive glucometer  diabetes management  breath analysis  volatile organic compounds (VOCs)  biomarkers  sensor design  machine learning  prototype development  clinical testing  glucose monitoring  multidisciplinary approach  patient comfort  quality of life.