https://github.com/tinybirdco/demo-ais

A demo processing AIS data using Tinybird, Dash, Pandas, and Plotly
https://github.com/tinybirdco/demo-ais

Last synced: 4 months ago
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A demo processing AIS data using Tinybird, Dash, Pandas, and Plotly

• Host: GitHub
• URL: https://github.com/tinybirdco/demo-ais
• Owner: tinybirdco
• License: mit
• Created: 2024-04-01T19:54:41.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-12-30T11:50:49.000Z (over 1 year ago)
• Last Synced: 2025-05-05T21:45:17.262Z (about 1 year ago)
• Language: Python
• Size: 457 KB
• Stars: 3
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md
  • License: LICENSE

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README

          
# AIS Explorer template for Tinybird

The AIS Explorer template provides a graphical exploratory interface for automatic identification system (AIS) data.

![Splash Image](assets/readme_splash.png)

For any given [MMSI](https://en.wikipedia.org/wiki/Maritime_Mobile_Service_Identity), the AIS Explorer shows the vessel's location over selected dates. You can represent location using latitude and longitude, or through [H3](https://h3geo.org/). You can adjust the H3 resolution to show more or less detail.

## Quick start

To deploy this template on Tinybird, click the following button:

[![Deploy to Tinybird](https://cdn.tinybird.co/static/images/Tinybird-Deploy-Button.svg)](https://app.tinybird.co/?starter_kit=https%3A%2F%2Fgithub.com%2Ftinybirdco%2Fdemo-ais)

Then clone or fork this repository and deploy the data project to Tinybird.

- Use noaa_uploader.sh to append as many of the zipped CSV files as you need to Tinybird for sample data.

- Run app.py to have a local app to explore some of the shipping data. The default values should work.

## Local deployment

To work on this project in your local environment, follow these steps:

1. Clone this repository.

2. Create a Python virtual env using `python -m venv .venv && source ./.venv/bin/activate`.

3. Install the Python dependencies by running `pip install -r requirements.txt`.

4. Open or create a [Tinybird](https://www.tinybird.co/) Workspace.

5. Open the [Tinybird Auth Token](https://www.tinybird.co/docs/get-started/administration/auth-tokens) page and copy the User Admin Token.

6. Run `tb auth` in the repo directory and paste the token.

7. Run `tb push` to establish the backend processing structure and serve the data APIs.

8. Use `noaa_uploader.sh` to append as many of the zipped CSV files as you need to Tinybird for sample data. Jan-May is about 1b rows. You might need `jq` installed: `sudo apt-get update && sudo apt-get install jq -y --no-install-recommends` or `brew install jq` for macOS.

9. Run `app.py` to have a local app to explore some of the shipping data. The default values should work.

You can also stream in live AIS data following the same format.

## Components

AIS Explorer uses [Dash and Plotly](https://dash.plotly.com/) for the map, [Pandas](https://pandas.pydata.org/) for the frontend data processing, and [Tinybird](https://ui.tinybird.co/signup) for the backend.

## Dataset

The dataset comes from [NOAA](https://coast.noaa.gov/htdata/CMSP/AISDataHandler/2020/index.html). It contains a few billion vessel observation samples from 2020.

> [!WARNING]

> NOAA provides this data for free, so don't abuse their download server.

## Credits

Created by [@Chaffelson](https://github.com/Chaffelson), [@juliavallina](https://github.com/juliavallina), [@sdairs](https://github.com/sdairs), and  [@rbarbadillo](https://github.com/rbarbadillo).