Future prediction for precautionary measures associated with heart-related issues based on IoT prototype

Cardiovascular disease (CVD) has become a significant cause of death around the world, with heart-related problems being a major contributor to this trend. It’s crucial to identify the signs and symptoms of potential health problems before they become severe. To address this issue, an IoT-based prototype has been proposed. This prototype utilizes an ML-based prediction model to provide precautionary measures for heart-related issues. It includes an IoT device that gathers real-time data from the user’s body, such as heart rate and ECG. This data is utilized to create an ML-based prediction model for heart-related problems. The model can alert the user of any potential heart-related risks. The proposed prototype is designed to offer a practical solution for the early detection of heart-related issues, therefore achieving a greater accuracy of 98.3% in lowering the death rate from heart disease than current methods. The results demonstrate that the suggested IoT-based prototype is useful for detecting various heart diseases and predicting future mortality rates compared to other existing machine-learning methods.