Quantum DAQ Platform

A configurable data acquisition and monitoring platform designed for BeagleBone Black, Linux, C++, Python, REST APIs, WebSockets, and real-time sensor visualization.

Current Version

Version: v0.1-python-daq-dashboard

This milestone implements a complete Python-based DAQ backend with simulated sensors, storage, REST API, WebSocket live streaming, and a browser dashboard.

Architecture

config.yaml
    ↓
Sensor Factory
    ↓
Sensor Simulators
    ↓
Acquisition Engines
    ↓
Broadcast Message Bus
    ├── Storage Worker → SQLite
    └── WebSocket Stream → Dashboard

Features

• Configurable sensors using YAML
• Temperature and pressure simulators
• Multi-sensor acquisition
• Threaded acquisition engines
• Broadcast message bus
• SQLite data storage
• REST API using FastAPI
• WebSocket live sample streaming
• Live browser dashboard using ECharts
• Sensor-specific live streams
• Sensor statistics endpoint
• Logging to console and file

Run

Install dependencies:

pip install -r requirements.txt

Start the DAQ platform and API:

python run.py

Open dashboard:

http://127.0.0.1:8000/dashboard

Open API docs:

http://127.0.0.1:8000/docs

Useful API Endpoints

GET /status
GET /samples/count
GET /samples/latest
GET /samples/recent
GET /sensors
GET /sensors/details
GET /sensors/{sensor_id}/samples
GET /sensors/{sensor_id}/statistics

WebSocket Endpoints

/ws/samples
/ws/samples/{sensor_id}
/ws/statistics/{sensor_id}

Example Sensor Configuration

sensors:
  - sensor_id: TEMP_001
    type: temperature
    location: LAB_001
    sample_rate_hz: 5

  - sensor_id: TEMP_002
    type: temperature
    location: LAB_002
    sample_rate_hz: 2

  - sensor_id: PRESS_001
    type: pressure
    location: LAB_001
    sample_rate_hz: 1