DataVisulaisationPlatform

A Flutter + Python system for real-time machine data acquisition and visualization.
Edge (Raspberry Pi/PLC) → MQTT → Cloud subscriber → Firestore (live) + MongoDB (history) → Flutter dashboard.

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Overview

• Edge: PLC → Raspberry Pi publishes telemetry via MQTT.
• Ingest: Cloud Python services subscribe to topics and dual-write to Firestore (real-time) and MongoDB (historical).
• UI: Flutter web/app for live charts, alarms, and CSV exports.
• (Optional): Small FastAPI helpers for API endpoints and CORS.

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Repository structure

DataVisulaisationPlatform/
├─ frontend_scripts/        # Flutter web/app (dashboards, charts, auth)
├─ aws_service_scripts/     # Python services: MQTT subscriber, writers, helpers
├─ PLC/                     # Edge publisher / PLC gateway scripts
├─ results/                 # Screens / output snapshots
├─ README.md
└─ LICENSE                  # MIT

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Features

• Live monitoring from Firestore (low-latency reads)
• Historical trends from MongoDB (long-term storage)
• Multi-parameter plotting with quick parameter selection
• Threshold-based alarms (client-side or server-side)
• CSV export for offline analysis
• Role-based access with Firebase Auth (admin/operator)

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Tech stack

• Edge/Gateway: Raspberry Pi, MQTT
• Backend: Python (MQTT subscriber, writers, optional FastAPI)
• Data: Firestore (real-time), MongoDB (history)
• Frontend: Flutter (Dart) web/app

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Prerequisites

• Flutter SDK installed (flutter doctor should pass)
• Python 3.10+
• Access to:
  • An MQTT broker
  • A MongoDB instance
  • A Firebase project (Auth + Firestore)

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Quick start

Adjust names/scripts to match your local setup; this repo groups code by responsibility to keep it portable.

1) Clone

git clone https://github.com/quanta-guy/DataVisulaisationPlatform.git
cd DataVisulaisationPlatform

2) Frontend (Flutter)

cd frontend_scripts
# set API/base URLs and Firebase client config in your environment or config file
flutter pub get
# for web
flutter run -d chrome
# for mobile, pick your device
# flutter run

3) Cloud subscriber & writers (Python)

cd ../aws_service_scripts
python -m venv .venv
# Windows: .venv\Scripts\activate
# Linux/macOS: source .venv/bin/activate
pip install -r requirements.txt
# export environment variables (see Configuration below)
# then start your subscriber / writer entrypoint script
python path_to_your_subscriber.py

4) Edge publisher (Raspberry Pi)

• In PLC/, configure the publisher with your MQTT_BROKER, MQTT_PORT, credentials, and base topic.
• Point the script to your PLC and publish telemetry at your chosen interval.
• Run as a systemd service for resilience (optional).

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Configuration

Create a .env or use your runtime environment for secrets:

MQTT (edge + cloud)

• MQTT_BROKER
• MQTT_PORT
• MQTT_USERNAME
• MQTT_PASSWORD
• MQTT_TOPIC_BASE

MongoDB (history)

• MONGODB_URI
• MONGODB_DB
• MONGODB_COLLECTION

Firestore / Firebase (real-time + auth)

• GOOGLE_APPLICATION_CREDENTIALS (service account JSON path for server components)
• Frontend Firebase config (apiKey, authDomain, projectId, etc.) via your Flutter config

Backend (if using FastAPI helpers)

• API_BASE_URL
• ALLOWED_ORIGINS

Keep secrets out of source control. Use .gitignore for .env and service account files.

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Data model (typical)

• Topics: site/{site_id}/line/{line_id}/machine/{machine_id}/{signal}
• Payload: JSON with timestamp, value, quality (example)
• Firestore: recent, frequently-read documents for live UI
• MongoDB: append-only timeseries collections for analytics

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Testing & linting

• Flutter: flutter test
• Python: add pytest and ruff (or flake8) to requirements-dev.txt and run locally or in CI

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Deployment notes

• Edge: run publisher as a systemd service on the Pi
• Cloud: run subscriber/writers as services (PM2, systemd, Docker, or your cloud’s app runner)
• Frontend: flutter build web and serve via any static host / CDN

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Roadmap

• Predictive maintenance models on MongoDB history
• Customizable dashboards by role
• Improved multi-tenant/topic configuration

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Contributor

Balaji Jayaprakash - @balajijp8 (https://github.com/balajijp8-boop)

Contributing

PRs welcome. Keep commits focused and add a short rationale in the description.
For issues, include repro steps, logs, and platform info.

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License

MIT — see LICENSE.