Low-Cost Non-Invasive Data Acquisition System for Diabetic Detection with IoT

Diabetes is a chronic disease that affects over 100 million people just in India and it's a severe challenge for Youngsters & Senior citizens. So, early detection of diabetes is crucial to prevent complications and improve patient outcomes. So, to eradicate it, low cost and fast prediction of diabetes is important. This paper we present a low-cost, non-invasive data acquisition system for diabetic detection using the Internet of Things (IoT). Our system utilizes a range of non-invasive sensors to collect physiological data from patients, including body temperature, SP02 level, and heart rate. This data is transmitted to a cloud platform called Thingspeak using a microcontroller (MCU) ESP32. The data collected from diabetic patient is used to create a dataset which can be used for analysis and training of advanced machine learning algorithms. The non-invasive nature of our system makes it user-friendly and accessible, allowing patients to monitor their health from the comfort of their own homes without the need for invasive devices that already exist in the market. Our results demonstrate the potential of our system for improving diabetic detection and management, providing a cost-effective and non-invasive solution for patients and healthcare providers.