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This repository contains code for various algorithms developed for a project of creating a smart traffic surveillance system as a part of the edge computing research.

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harshilshah4251/research_fall_2018

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Set up virtual env and install dependencies required for this repository using this command.

virtualenv --no-site-packages --distribute .env &&\ source .env/bin/activate &&\ pip install -r requirements.txt

Running the project

  1. Generate camera locations using the available taxi data.
    • Inside of project directory run python3 camera-locations-generator.py.
    • This will randomly select a sample of points from the taxi traces and place cameras at those points. The output is stored in jsons/camera-locations-generated.json.
  2. Run main.py which will read taxi traces line by line and map the taxis to the cameras that detected it.
  3. Run plot_on_map.py which will update the map.html file with camera location and vehicle detection markers.
    • Inside the project directory, run python3 plot_on_map.py.

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This repository contains code for various algorithms developed for a project of creating a smart traffic surveillance system as a part of the edge computing research.

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