基于集成IoT和Fog计算环境的自动诊断心脏疾病的集成深度学习智能医疗系统.zip

# HealthFog An ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated IoT and Fog computing environments <div align="center"> <img src="https://github.com/Cloudslab/HealthFog/blob/master/HeartModel/fog-arch.jpg" width="700" align="middle"> </div> ## 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: <b>Note:</b> 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 <i>Install-scripts/fogbus-install-generic.sh</i> script in a linux device. 2. Clone HealthFog repo at <i>C:/xampp/htdocs/</i> (in windows) or <i>var/www/html/</i> (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 <i>config.txt</i> 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 <i>cloud.txt</i> (each in a new line). Now download and install <i>Android/FastHeartTest.apk</i> 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/)