Telematics HeatMap

This project provides a heatmap visualization library for telematics data. The project aims to make it easier to render data visualizations of data contained in CSV files. To view heatmaps using this web application, upload any CSV file with data points containing atleast column fields named lat and lon (case insenstive, in any order and CSV can contain other column fields).

Preview of Running Application

Technologies used

• Docker - packages application, runtime, configurations and dependencies.
• Flask - actual telematics web application.
• uwsgi - web server for the flask application.
• Nginx - reverse proxy to the uwsgi web server.
• Google Maps JS API - map component used for visualization.

Input Rules

• Any CSV file is accepted.
• CSV files should contain columns with at-most 2 columns that contain the following substrings lat and lon. Example column names that will be accepted as valid input are Lat, Lon, lat, lon, Latitude, Longitude, MyLatitudes, etc.
• CSV files can contain other data columns. This app will only scrap the 2 lat and lon sub-stringed columns it expects.
• The ordering and relative positions of the lat and lon sub-stringed columns does not matter.

Additional Application Features

This app also comes with the following functionality:

• Toggling heatmap on and off.
• Changing gradient of heatmap visualization.
• Changing radius of heatmap visualization.
• Changing opacity of heatmap visualization.

Getting Started

To use Google Maps in the front-end web appliacation, a Google Maps Javascript API key is required. The instructions of obtaining the API key are documented here.

• Also, ensure that you are running in a Python 3 environment.

Running the Application In Development Environment

1. Setup virtual environment

python3 -m venv env
source ./env/bin/activate

2. Setup the MAPS_API_KEY environment variable in your virtual environment :

export MAPS_API_KEY=<MAPS_API_KEY_FROM_GOOGLE>

3. Install dependencies required by application :

cd application

pip install --no-cache-dir -r requirements.txt

4. Run the application locally:

python app.py

5. Access the front-end web application: In your web browser, navigate to the address http://127.0.0.1:5000/ in a web browser and upload a CSV file with your telematics data.

Running the Application in Docker

1. To build application, run:

docker build -t heatmapimage .

2. To run application, run:

docker run -d --name heatmaps -e MAPS_API_KEY=<MAPS_API_KEY_FROM_GOOGLE> -p 1337:80 heatmapimage

You should be able to check access the web front end of the application on http://localhost:1337/ . Submit a CSV file with your telematics data and click upload to visualize your data.