OUTFIT

OUTFIT - Dynamic Road Noise Maps Based on Crowdsourced Data and Represented in Digital Twins

The OUTFIT PRIN 2022 project aims to dynamically represent road traffic noise (RTN) in a Digital Twin (DT) model by optimizing the data flow related to noise levels and citizen perception.

Overview

This repository provides tools to:

• Collect raw data via API calls to the Google Maps Directions service.
• Process this data to generate perceived sound power at receivers located on building facades in the area of interest.

Installation

Requirements

This project requires the following Python packages:

• python-dotenv
• requests
• numpy
• pyarrow
• pandas
• wxpython
• pyinstaller

It is recommended to install these packages inside a Python virtual environment using conda or venv.

You can find instructions to install Conda here: Conda Installation You can find instructions to install venv (built into Python 3) here: venv Documentation

Tip: You can use pyenv.bat (Windows) or source pyenv.sh (Linux/macOS) to automatically install Miniconda, set up the environment, and enter it. Alternatively, you can use bundle.bat (Windows, Linux/macOS support coming soon) to generate a standalone execution file for the entire project.

Using Conda

Once Conda is installed, create and activate a new environment with:

conda env create -f environment.yml
conda activate outfit

This will automatically install all required packages defined in environment.yml.

Using venv

venv is a built-in Python module for creating isolated environments. Using a virtual environment ensures that your project dependencies do not conflict with other Python projects on your system. Steps to create a venv, install packages, and enter the environment:

Windows CMD

python -m venv outfit
.\outfit\Scripts\activate
pip install -r requirements.txt

Windows PowerShell

python -m venv outfit
.\outfit\Scripts\Activate.ps1
pip install -r requirements.txt

macOS and Linux

python -m venv outfit
source outfit/bin/activate
pip install -r requirements.txt

Usage

You can run the project in two ways:

1. Download the executable Download the OUTFIT.exe file and run it directly.

2. Run with Python Install the required packages (see Installation) and run the GUI with:

   python src/outfit.py
   
   

Using the GUI

Once the GUI appears, you will need to provide the following information:

• API Key: your Google APIs key;
• Prefix: a name to identify your collected data;
• data: the path of the CSV file containing the streets for which data will be collected;
• Data Range: the date and time range over which the data will be collected.
• Interval: the time in minutes between two consecutive API calls while collecting street information.

After filling in all the required fields:

• Click Start Schedule to begin the data collection task.
• Click Remove Schedules to delete all scheduled tasks.