Abstract
Abstract: This research paper explores the potential of IoT systems to predict diabetes, which is a chronic disease that affects millions of people worldwide. The paper reviews existing literature on IoT systems for diabetes prediction and proposes a new system that can be implemented in resource-limited settings. The proposed system comprises a wearable device that monitors physiological data, a mobile application that analyzes the data using machine learning algorithms, and personalized recommendations to improve diabetes risk scores. The paper concludes that IoT systems offer a convenient way to predict diabetes risk and enable users to take proactive measures to manage their health. Further research is needed to evaluate the feasibility and effectiveness of the proposed system in real-world settings
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