HealthFog: An Ensemble Deep Learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing Environments

TL;DR

HealthFog is a novel ensemble deep learning framework integrated with fog computing to enable low-latency, accurate, and energy-efficient automatic heart disease diagnosis in IoT-enabled healthcare environments.

Contribution

The paper introduces HealthFog, a new ensemble deep learning system deployed on fog computing devices for real-time heart disease diagnosis, addressing latency and accuracy limitations of existing models.

Findings

HealthFog achieves high diagnostic accuracy for heart diseases.

The system reduces latency and energy consumption compared to traditional cloud solutions.

Performance is validated on real IoT and fog computing setups.

Abstract

Cloud computing provides resources over the Internet and allows a plethora of applications to be deployed to provide services for different industries. The major bottleneck being faced currently in these cloud frameworks is their limited scalability and hence inability to cater to the requirements of centralized Internet of Things (IoT) based compute environments. The main reason for this is that latency-sensitive applications like health monitoring and surveillance systems now require computation over large amounts of data (Big Data) transferred to centralized database and from database to cloud data centers which leads to drop in performance of such systems. The new paradigms of fog and edge computing provide innovative solutions by bringing resources closer to the user and provide low latency and energy-efficient solutions for data processing compared to cloud domains. Still, the current fog models have many limitations and focus from a limited perspective on either accuracy of results or reduced response time but not both. We proposed a novel framework called HealthFog for integrating ensemble deep learning in Edge computing devices and deployed it for a real-life application of automatic Heart Disease analysis. HealthFog delivers healthcare as a fog service using IoT devices and efficiently manages the data of heart patients, which comes as user requests. Fog-enabled cloud framework, FogBus is used to deploy and test the performance of the proposed model in terms of power consumption, network bandwidth, latency, jitter, accuracy and execution time. HealthFog is configurable to various operation modes that provide the best Quality of Service or prediction accuracy, as required, in diverse fog computation scenarios and for different user requirements.