Architecture

NoiseModelling is the name of the application that allows to calculate noise maps (notably through a Graphical User Interface). But did you know that it is also the name of different calculation libraries?

The documentation below presents the architecture of NoiseModelling with its different bricks and the ways to launch it:

  1. NoiseModelling libraries

  2. Database connection

  3. NoiseModelling with a Graphical User Interface (GUI)

  4. NoiseModelling with command line

  5. NoiseModelling with Docker

_images/architecture.png

1. NoiseModelling libraries

NoiseModelling is made of 5 main librairies:

  • noisemodelling-emission : to determine the noise emission

  • noisemodelling-pathfinder : to determine the noise path

  • noisemodelling-propagation : to calculate the noise propagation

  • noisemodelling-jdbc : to connect NoiseModelling to a database

  • noisemodelling-scripts : Groovy scripts and web server

These libraries may be used independently of each other. Note that the noisemodelling-jdbc library (JDBC = Java DataBase Connectivity) is central since it allows the three others to communicate with each other as soon as the data are stored in a database (which is the default situation).

2. Database connection

Thanks to the noisemodelling-jdbc library, NoiseModelling can access and communicate with databases. This system is quite adapted to store, manage and process (spatial) data. Here, the user has the choice between to database (free, open-source and powerful) couples:

In both cases, database can be local or remote.

3. NoiseModelling with a GUI

NoiseModelling has a Graphical User Interface (GUI). It is accessible through a web browser and the web page is named “WPS Builder”.

In order for “WPS Builder” to communicate with the NoiseModelling libraries, we use a standard name Web Processing Service (Defined by the Open Geospatial Consortium OGC) API to execute WPS scripts. Theses scripts are written in the Groovy language.

You can see NoiseModelling with a GUI in action in the page “Get Started - GUI”.

4. NoiseModelling with command lines

You can use NoiseModelling with command lines. To do so,

  1. Open a terminal

  2. Go in the NoiseModelling directory

  3. Call the WPS .groovy script you want, with the needed arguments

Note

The .groovy script may be simple (the ones already provided with NoiseModelling, executing one task) or complex (tailor made by users and calling one or many .groovy script(s)).

Note

No need to launch / start the application as we do with web server. Here the NoiseModelling libraries are called directly for each instructions.

Examples can be found in the page “NoiseModelling client line interface (CLI)”.

5. Docker Setup

When a developer uses Docker, he creates an application or service, which he then bundles together with the associated dependencies in a container image. An image is a static representation of the application or service, its configuration and dependencies.

Available versions

The Docker images are published on our Github repository. It is the best way to safely host NoiseModelling on a public server. Be aware that a registered user may be able to run a privilege escalation attack through the usage of scripts/SQL, so you should add only trusted users.

On the root of this repository you can find an example docker compose.

You can edit the following environment variables:

  • PROXY_BASE_URL : If you have a domain name you can use the your domain name instead of localhost

  • ROOT_URL : By default the service is accessible from the path /noisemodelling but you can change it by using the environment variable ROOT_URL (empty to use the base url)

  • UNSECURE_MODE : By default the registration is enabled (with TOTP). If you use this docker image locally, you can disable the registration by setting the environment variable UNSECURE_MODE in the docker-compose.yml file to true.

Dependencies

Install Docker or Podman on your system

Running

Download the file docker-compose.yml and run this command in the same folder:

docker compose up -d

or

podman compose up -d

Follow the instructions of the logs in order to register the administrator account (if not in unsecure mode).

docker compose logs noisemodelling

or

podman compose logs noisemodelling