https://github.com/cloudslab/healthfog
[FGCS'20] An ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated IoT and Fog computing environments
https://github.com/cloudslab/healthfog
deep-learning fog-computing fogbus healthcare
Last synced: 5 months ago
JSON representation
[FGCS'20] An ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated IoT and Fog computing environments
- Host: GitHub
- URL: https://github.com/cloudslab/healthfog
- Owner: Cloudslab
- License: gpl-3.0
- Created: 2019-06-07T04:38:25.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2020-12-16T11:33:40.000Z (over 5 years ago)
- Last Synced: 2025-09-10T04:06:50.407Z (9 months ago)
- Topics: deep-learning, fog-computing, fogbus, healthcare
- Language: PHP
- Homepage:
- Size: 11.7 MB
- Stars: 26
- Watchers: 3
- Forks: 9
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# HealthFog
An ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated IoT and Fog computing environments
## Quick installation guide
HealthFog uses a master-slave design as shown in the figure above. To setup HealthFog in your fog environment follow these steps:
Note: You need atleast two windows/linux systems with python 3. Follow the following steps in each fog node (master and worker):
1. Install [xampp](https://www.apachefriends.org/xampp-files/7.2.30/xampp-windows-x64-7.2.30-0-VC15-installer.exe) and run Apache server in windows or use Install-scripts/fogbus-install-generic.sh script in a linux device.
2. Clone HealthFog repo at C:/xampp/htdocs/ (in windows) or var/www/html/ (in linux) and rename the folder as *HealthFog*.
3. Change directory to the HealthFog repo folder.
4. Run ```python3 -m pip install -r requirements.txt```.
5. Run ```cd HeartModel && python3 MasterInterface.py```.
6. Run Apache service from Xampp control panel.
Follow these steps in master node:
1. Update config.txt with IP addresses of all worker nodes (each in a new line) after the first line of 'EnableMaster DisableAneka'.
2. If connected to cloud using VPN add cloud virtual IP, otherwise add public IP addresses in cloud.txt (each in a new line).
Now download and install Android/FastHeartTest.apk in an android device and enter master IP address to begin healthcare analysis!
## Developer
[Shreshth Tuli](https://www.github.com/shreshthtuli) (shreshthtuli@gmail.com)
## Cite this work
```
@article{tuli2020healthfog,
title={{HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments}},
author={Tuli, Shreshth and Basumatary, Nipam and Gill, Sukhpal Singh and Kahani, Mohsen and Arya, Rajesh Chand and Wander, Gurpreet Singh and Buyya, Rajkumar},
journal={Future Generation Computer Systems},
volume={104},
pages={187--200},
year={2020},
publisher={Elsevier}
}
```
## References
* Shreshth Tuli, Redowan Mahmud, Shikhar Tuli, and Rajkumar Buyya, [FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing.](http://buyya.com/papers/FogBus-JSS.pdf) Journal of Systems and Software (JSS), Volume 154, Pages: 22-36, ISSN: 0164-1212, Elsevier Press, Amsterdam, The Netherlands, August 2019.
* **Shreshth Tuli, Nipam Basumatary, Sukhpal Singh Gill, Mohsen Kahani, Rajesh Chand Arya, Gurpreet Singh Wander, and Rajkumar Buyya, [HealthFog: An Ensemble Deep Learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing Environments](http://buyya.com/papers/HealthFog.pdf), Future Generation Computer Systems (FGCS), Volume 104, Pages: 187-200, ISSN: 0167-739X, Elsevier Press, Amsterdam, The Netherlands, March 2020.**
* Shreshth Tuli, Nipam Basumatary, and Rajkumar Buyya, [EdgeLens: Deep Learning based Object Detection in Integrated IoT, Fog and Cloud Computing Environments](http://buyya.com/papers/EdgeLensAnekaCloud2019.pdf), Proceedings of the 4th IEEE International Conference on Information Systems and Computer Networks (ISCON 2019, IEEE Press, USA), Mathura, India, November 21-22, 2019.
[](http://cloudbus.org/)