A Healthcare System for Cardiac Disease Diagnosis Using Distributed Computing

Abstract

The sector of health care makes extensive use of cloud computing and wireless devices that are based on the internet of things.  These kinds of wireless and wearable sensors are being used to monitor patients who are at risk for developing chronic diseases. This not only shields patients from attacks that come out of the blue but also makes it easier for them to monitor their treatment regimen. However, the quantity of data acquired from numerous sensors is substantial, and if the data is kept in a centralised location, there is a possibility that the power supply will fail. As a result, in this paper, we suggest the creation of a technology called Smart Fog, which is capable of edge-fog computing and would be able to detect and diagnose heart patients at an early stage. It is anticipated that the overall efficacy of the system would improve as a result of the implementation of the suggested model, which is founded on the concepts of distributed computing and deep learning. With the application of the distributed computing approach, the risk associated with a single point of failure would be eliminated, and in addition, a less amount of data would be required to transfer the information between the cloud and the sensors.