Enhancing Diabetes Management: A Machine Learning-Enabled IoT Framework for Early Detection

Diabetes has to be identified and treated as soon as possible to prevent serious consequences. In order to forecast and monitor diabetes in real time, this effort integrates machine learning with the Internet of Things (IoT). Advanced sensors gather patient data, which is subsequently analysed and transferred to a cloud-based healthcare workstation using an Arduino UNO-based system. Out of all the machine learning techniques examined, the Artificial Neural Network (ANN) had the best accuracy (73.38%), recall rate (62%), and precision (63%). This IoT-enabled strategy offers a low-cost way to improve early diabetes identification and treatment, continuously monitor health, and improve patient outcomes through proactive, personalised healthcare.