An IoT Enabled Computational Model and Application Development for Monitoring Cardiovascular Risks

The Internet of Things (IoT) has opened up a wide array of possibilities for healthcare and medical practitioners alike. This technology offers an effective platform to monitor and manage various aspects of a person's health, including cardiovascular risks. In this context, a computational model and application development play a significant role in monitoring risks, optimizing treatments, and creating personalized care plans. The model explores various parameters such as lifestyle, diet, and medications to predict the potential risks that may endanger a person's life. Artificial Intelligence algorithms are used to optimize the performance of the model. The techniques used for data collection, analysis, and interpretation have been adapted from data science, which allows for more accurate predictions. The data collected from the model is used to develop an application that can be used to monitor the health of the patient and provide appropriate advice on medication, diet, and lifestyle. This application can be used by both the medical practitioner and the patient, providing them with useful information on an ongoing basis. By combining the skills of design, engineering, and data science, the model and application can be used to improve outcomes and reduce the costs associated with cardiovascular treatment. It can also help to reduce the risks associated with heart disease and stroke, and create a better quality of life for patients suffering from various heart-related conditions.