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GRD-TRT-BUF-4I: Ground Truth Buffer for Idling

An implementation of GRD-TRT-BUF-4I from the paper "Global Geolocated Realtime Data of Interfleet Urban Transit Bus Idling." The system detects, stores, and visualizes urban transit bus idling data in realtime. It is designed using containerized microservices and is configurable to deploy on any cloud-based platform. Each microservice is listed below with a brief description.

Version: Imhotep 0.1.3
Updated: November 2024

Microservices

  • Extract (ext): Collects and parses protocol buffers from GTFS Realtime sources.
  • Subset (sub): Filters and computes idling data for websocket streaming.
  • Write (wrt): Inserts the idling data into persistent storage.
  • Database (db): Manages idling data storage and retrieval.
  • Read (rdb): Retrieves stored idling data from database. Also contains data tests.
  • Interface (gui): Frontend idling data visualization and retrieval.

Predeployed Endpoints

  • Extract (ext): Use the /extract route for GTFS Realtime protobuf data and base route for testing.

    https://idling-extract.redpebble-aeec30b4.westus.azurecontainerapps.io/

  • Subset (sub): Connect to the base route using the Socket.IO request type and listen for websocket events title events.

    https://idling-subset.redpebble-aeec30b4.westus.azurecontainerapps.io/

  • Read (rdb): Please see Usage for usage notes. Use the base route for testing.

    https://idling-read.redpebble-aeec30b4.westus.azurecontainerapps.io/

  • Interface (gui): Simply navigate to the base route in your browser to access the frontend.

    https://idling-interface.redpebble-aeec30b4.westus.azurecontainerapps.io/

Dependencies

  • Docker Desktop (Latest)
  • OS: Ubuntu 20.04
  • Language: Python 3.8
  • Web App: Flask 2.3.1 / Quart 0.18.3
  • WSGI/ASGI: Gunicorn / Uvicorn (Latest)
  • Proxy Server: Nginx (Latest)
  • Database: PostgreSQL 16
  • Frontend: React (17.0.2), Deck GL (8.9.33)

Note: All dependencies are automatically installed when built with Docker.

Requirements

Repository Structure

The repository follows the structure below:

├─ ext                   ## extract microservice
├─ gui                   ## interface microservice
├─ rdb                   ## read microservice and data tests
├─ sub                   ## subset microservice
├─ wrt                   ## write microservice
├─ .dockerignore         ## excluded files in docker
├─ .gitignore            ## excluded files in git
├─ docker-compose.yml    ## container orchestration
├─ LICENSE               ## software license
├─ README.md             ## documentation

Backend

Each backend microservice is structured to follow the pattern below:

├─ ...
├─ abc
│   ├─ conf              ## config files
│   ├─ src               ## source code
│   ├─ test              ## test code
│   ├─ .env.example      ## env vars
│   ├─ app.py            ## main app
│   ├─ Dockerfile        ## container
│   ├─ README.md         ## documentation
│   ├─ requirements.txt  ## dependencies
│   └─ start.sh          ## startup script
├─ ...

Frontend

The frontend microservice follows the structure below:

├─ ...
├─ gui
│   ├─ conf              ## config files
│   ├─ public            ## test code
│   ├─ src               ## source code
│   ├─ .env.example      ## env vars
│   ├─ Dockerfile        ## container
│   ├─ package-lock.json ## dependencies
│   ├─ package.json      ## dependencies
│   ├─ README.md         ## documentation
│   └─ start.sh          ## startup script
├─ ...

Installation

  1. Acquire API Keys

    There are two categories of API keys that are required. More information on how to obtain them is here:

  2. Install Docker

    Ensure that Docker Desktop is installed on your local machine. You can download it here:

    https://docs.docker.com/get-docker/

  3. Clone Repository

    Clone this repository to a directory on your local machine.

    git clone

    Navigate to the project folder.

    cd <path to project folder>

  4. Build Container Images

    Build the container images.

    docker-compose up --build

    This command will also run the container images for each microservice, including the database.

    It may take awhile to complete the build process for each microservice.

Port Conventions

The design pattern follows these port conventions:

  • 8080: Extract (ext)
  • 7080: Subset (sub)
  • 6080: Write (wrt)
  • 5432: Database (db)
  • 4080: Read (rdb)
  • 3080: Interface (int)

Usage

  1. Connect to Websocket

    Ensure the Extract and Subset microservices are running. Use an API client like Postman or similar and connect to the endpoint ws://localhost:7080 using Socket.IO.

    Listen for the events titled events. There should be a continuous stream of idling data every 30 seconds in the following format:

    {
    "iata_id": "",
    "vehicle_id": "",
    "route_id": "",
    "trip_id": "",
    "latitude": 0.01,
    "longitude": -0.01,
    "datetime": 123,
    "duration": 123
}

  2. Read Database

    Ensure the Read and Database microservices are running and have had sufficient time to collect an historical record of data.

    Using the endpoint http://localhost:4080/ specify one of the three following routes:

    • /agency: Retrieves transit agency table.
    • /events: Retrieves idling events table
    • /idle: Joins agency table with events table.

    Parameters for each route can be specified as such:

    • format: geojson or csv (e.g. format=csv).
    • iata_id: IATA code of transit agency (e.g. iata_id=NYC).

    Additional parameters that apply to the /agency and /idle routes:

    • agency: Name of transit agency.
    • city: City of transit agency.
    • country: Country of transit agency.
    • region: Region of transit agency.
    • continent: Continent of transit agency.

    Additional parameters that apply to /events and /idle routes:

    • vehicle_id: Vehicle ID of idling events.
    • route_id: Route ID of idling events.
    • trip_id: Trip ID of idling events.
    • datetime: POSIX time of idling events.
    • start_datetime: Start POSIX time of idling events.
    • end_datetime: End POSIX time of idling events.
    • duration: Duration of idling events (seconds).
    • min_duration: Minimum duration of idling events (seconds).
    • max_duration: Maximum duration of idling events (seconds).

    For example, to retrieve all idling events in New York City in CSV format:

    http://localhost:4080/idle?format=csv&iata_id=NYC

    or to retrieve all idling events in Montreal longer than 5 minutes in GeoJSON format:

    http://localhost:4080/idle?format=geojson&iata_id=YUL&min_duration=300

  3. Browse Interface

    Ensure the Interface microservice is running. Navigate to http://localhost:3080 in your browser to access the frontend interface.

Citations

@article{Kunz_2024,
  title         = {{Global Geolocated Realtime Data of Interfleet Urban Transit Bus Idling}},
  author        = {Nichlas Kunz and H. Oliver Gao},
  eprint        = {2403.03489},
  year          = {2024},
  archivePrefix = {arXiv},
  primaryClass  = {eess.SY},
  howpublished  = "\url{https://arxiv.org/abs/2403.03489}"
}

Contributions

GRD-TRT-BUF-4I is open for improvements and maintenance. Your help is valued to make the system better for everyone.

Contact

Nick Kunz, Cornell University: nhk37@cornell.edu

License

© Nick Kunz, 2024. Licensed under the General Public License v3.0 (GPLv3).

References

Kunz, N., Gao, H. O. (2024). Global Geolocated Realtime Data of Interfleet Urban Transit Bus Idling. Preprint. arXiv:5451982 [eess.SY]. https://arxiv.org/abs/2403.03489.