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@article{180145,
        author = {Gnanapriya S M.E and Sharmila M M.E and Arthi R and Preethi K and Sandhiya M and Sarathi M},
        title = {Non-Invasive Blood Glucose Monitoring System with Sensor Technology},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {323-329},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180145},
        abstract = {Diabetes management often relies on invasive 
finger-prick tests, which are painful, costly, and 
inconvenient for continuous monitoring. This paper 
presents an IoT-enabled, non-invasive blood glucose 
monitoring system that measures glucose levels in real 
time without blood samples. The system employs optical 
sensors, electromagnetic fields, and bioimpedance 
techniques to detect glucose concentrations through the 
skin. An ESP32 microcontroller processes the data and 
transmits it to a cloud platform via Wi-Fi. Real-time 
glucose readings, alerts, and historical trends are 
displayed using a mobile app like Blynk. Machine 
learning algorithms enhance predictive capabilities by 
analysing past glucose trends, enabling proactive 
diabetes management. The integration of IoT ensures 
seamless data storage, remote monitoring, and 
telemedicine support. Compared to traditional 
methods, this solution is painless, cost-effective, and 
user-friendly. Future improvements using AI-driven 
analytics and advanced sensor technology may further 
enhance system accuracy and efficiency. The proposed 
system aims to revolutionize diabetes care and improve 
patient quality of life.},
        keywords = {IoT, non-invasive glucose monitoring,  ESP32, near-infrared spectroscopy, machine learning,  cloud computing, real-time monitoring, diabetes  management.},
        month = {May},
        }