IoT-Based Non-Invasive Monitoring of Blood Sugar Levels with Early Warning Mechanism

Zubair Khan; Ehsan Khan; Muhammad Tariq Tanoli; Muhammad Ashan; Muhammad Amir; Bilal Ur Rehman; Kifayat Ullah Bangash; Muhammad Farooq; Muhammad Iftikhar Khan

Authors

Zubair Khan Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
Ehsan Khan Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
Muhammad Tariq Tanoli Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
Muhammad Ashan Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
Muhammad Amir Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
Bilal Ur Rehman Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan https://orcid.org/0000-0003-2349-7518
Kifayat Ullah Bangash Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
Muhammad Farooq Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
Muhammad Iftikhar Khan Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan

Keywords:

Arduino, Non-invasive monitoring, Internet of Things (IoT), Glucose level detection, Diabetes management

Abstract

This research presents the design and implementation of a non-invasive sugar level monitoring system with an early warning mechanism using embedded systems and Internet of Things (IoT) technologies. The system integrates an Arduino Uno microcontroller with sensors such as the MLX90614 infrared temperature sensor, MAX30102 blood oxygen and heart rate sensor to monitor vital health parameters. The system correlates temperature, blood oxygen levels, heart rate, and glucose levels to provide early warnings for high or low sugar conditions. Experimental results demonstrate the system's accuracy, reliability, and effectiveness in providing real-time health data. Also, this research highlights the potential of non-invasive health monitoring systems in diabetes management and paves the way for future advancements in IoT-based healthcare solutions.

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