A real-time vehicle telemetry pipeline featuring anomaly detection, live dashboards, and scalable event streaming — powered by FastAPI, Kafka, PostgreSQL, and Streamlit.
(Add a screenshot or GIF of your dashboard here)
- Real-time telemetry ingestion from simulated vehicles
- Fault detection and reporting with severity levels
- RESTful API with automatic OpenAPI documentation
- Interactive dashboard for real-time monitoring
- Anomaly detection for identifying unusual patterns
- Kafka integration for scalable data streaming
+---------------------+ +-------------------+ +----------------------+
| Data Generator | --> | FastAPI API | --> | PostgreSQL DB |
| (Simulation) | | (Telemetry Ingest)| | (Data Storage) |
+---------------------+ +-------------------+ +----------------------+
| | |
| | |
v v v
+---------------------+ +-------------------+ +----------------------+
| Streamlit | | Kafka | | Anomaly Detection |
| Dashboard | | (Optional) | | (Pattern Analysis) |
+---------------------+ +-------------------+ +----------------------+
- Python 3.8+
- pip or Poetry
- PostgreSQL (optional for demo mode)
- Kafka (optional, only required for streaming mode)
Clone and setup:
cd CarSafe
python -m venv venv
.\venv\Scripts\activate # Windows
pip install -r requirements.txtuvicorn api.main:app --reload
python generator/main.py (Start the Data Generator)
streamlit run dashboard/app.py (Start the Dashboard)Once the API is running:
- Swagger UI → http://localhost:8000/docs
- ReDoc → http://localhost:8000/redoc
docker-compose up --build