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# W4H-Preview | ||
This document is for the preview of Wearables for Health (W4H) toolkit. | ||
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This Toolkit is available as a Docker image, which can be easily pulled from [Docker Hub](https://hub.docker.com/r/uscimsc/w4h). This containerized version includes all the necessary components and dependencies, making it simple to set up and use the toolkit. | ||
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### Pulling the W4H Docker Image | ||
To get started with the W4H Toolkit, follow these steps: | ||
1. Get [Docker](https://docs.docker.com/engine/install/) for your OS. | ||
2. Install Docker engine. | ||
3. Open a terminal or command prompt. | ||
4. Verify Docker installation using: | ||
```bash | ||
docker --version | ||
``` | ||
5. Pull the W4H Docker image from Docker hub by running the following command: | ||
```bash | ||
docker pull usc-imsc:w4h-toolkit-preview | ||
``` | ||
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The W4H toolkit provides the following components: | ||
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**Streamlit Dashboard** : An integrated interface for GeoMTS data extraction, presentation & analysis. It facilitates the analysis of both streaming & stored data. | ||
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**Database supporting GeoMTS**: A postgres database with TimescaleDB for temporal data management, PostGIS for spatial data management & FFT postgres for aggregate queries on time series data. | ||
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**Notebooks**: A collection of sample Jupyter notebooks that help analyse compliance using Pandas & Pyspark . | ||
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## Accessing the Dashboard | ||
After running the docker container, the dashboard is available at http://localhost:8501/ | ||
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A default account is configured in the preview for the initial testing. Credentials for it are: | ||
``` | ||
username: admin | ||
password: admin | ||
``` | ||
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This dashboard provides the following buttons: | ||
+ ImportHub: The ImportHub allows to integrate offfline datasets into the W4H platform. It aligns the data with GeoMTS schema & automatically maps attributes. | ||
+ Input Page : It allows creation of queries for the data by selecting the required database & transforming the data using filters for visualizations. | ||
+ Result Page: It takes you to the result of the query. It provides outlier detection, comparative analysis between different groups of subjects, health insights, etc. | ||
+ Query History: You can browse through the history of your visualizations using the Query History Button. | ||
+ Getting Started: It provides a detailed tutorial on how to get started with the preview. | ||
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## Accessing Jupyter Notebooks | ||
To access the Jupyter notebooks in the W4H Toolkit, follow these steps: | ||
1. Navigate to http://localhost:8888 in browser | ||
2. When prompted for authentication, use: | ||
``` | ||
token: admin | ||
``` | ||
3. Once logged in, you'll see the Jupyter notebook interface with access to the /app/notebooks/ directory, which contains the sample notebooks provided by the W4H Toolkit. | ||
4. You can now open existing notebooks or create new ones to work with the W4H datasets. | ||
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## Accessing the Database | ||
The postgres database can be accessed using tools like pgadmin or psql. | ||
To access the database using pgadmin use the following steps: | ||
1. Download & install [pgadmin](https://www.pgadmin.org/) & launch it. | ||
2. In the pgAdmin dashboard, click on "Add New Server" or right-click on "Servers" in the browser pane and select "Create" > "Server...". | ||
3. In the "Create - Server" dialog, fill in the following details: | ||
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General Tab: | ||
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Name: W4H Database (or any name you prefer) | ||
Connection Tab: | ||
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Host name/address: localhost | ||
Port: 5432 | ||
Maintenance database: postgres | ||
Username: postgres | ||
Password: postgres | ||
4. Save to establish the connection. Once connected, you should see the server appear in the browser pane. | ||
5. To interact with the database: | ||
+ Expand the sample database to view its schemas, tables, and other objects. | ||
+ Use the Query Tool (accessible via Tools > Query Tool) to run SQL queries. | ||
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Move this all thing in the main README.md Then explain at the end that the rest of documentation is work in progress.