A premium, high-performance IoT intelligence platform for real-time sensor telemetry and neural visualization.
Velesync is a professional-grade IoT ecosystem designed to bridge the gap between raw hardware telemetry and high-fidelity intelligence. Utilizing a state-of-the-art Glassmorphism interface and a high-concurrency FastAPI backbone, Velesync provides a robust, scalable foundation for modern industrial, scientific, and smart-infrastructure deployments.
Velesync utilizes a curated selection of high-performance technologies, pinned to their latest stable releases for maximum reliability:
- FastAPI (v0.136.1): Asynchronous, high-performance web framework for Python.
- SQLAlchemy (v2.0.49): Professional-grade SQL toolkit and Object-Relational Mapper.
- Paho-MQTT (v2.1.0): Industrial-standard MQTT client implementing
CallbackAPIVersion.VERSION2. - Uvicorn (v0.46.0): Lightning-fast ASGI server implementation.
- Eclipse Mosquitto (v2.1.2): Lightweight and scalable MQTT message broker.
- Docker & Compose: Containerized orchestration for deterministic deployments.
- Nginx (v1.27.0-alpine): High-performance reverse proxy and static file server.
- Vanilla JS/CSS3: Zero-dependency frontend logic for ultra-low latency.
- Chart.js (v4.5.1): Premium, responsive charting with custom neural gradients.
- Design System: Custom Glassmorphism theme utilizing Deep Obsidian (
#0B0E14) and Electric Cobalt (#2E5BFF).
The recommended way to run Velesync is via Docker Compose. This initializes the entire stack—Backend, MQTT Broker, and Frontend—automatically.
# Clone and enter the repository
git clone https://github.com/your-username/velesync.git
cd velesync
# Launch the neural stack
docker-compose up -d --build- Intelligence Dashboard: http://localhost:80
- API Documentation: http://localhost:8000/docs
- MQTT Neural Bridge:
localhost:1883
For local debugging or modification of the core intelligence:
# Setup Python environmentcd backend
python -m venv venv
source venv/bin/activate # Or venv\Scripts\activate on Windows# Install pinned dependencies
pip install -r requirements.txt
# Start the API
uvicorn main:app --reload --port 8000To instantly visualize the platform's capabilities without hardware:
Option A: Browser Demo (No Setup)
- Open the dashboard at http://localhost:80.
- Click "START DEMO MODE" in the top navbar.
- Observe real-time neural data generation and visualization.
Option B: System-Wide Simulation (Full Stack Test)
- Ensure the stack is running via Docker.
- Run the Python simulator:
python scripts/simulate_device.py
- This will broadcast live telemetry across the MQTT bridge, populating the real database and dashboard.
Velesync is hardware-agnostic, supporting any device capable of MQTT. We recommend the following stable libraries for ESP32/Arduino development:
- ArduinoJson (v7.4.3): For efficient neural packet serialization.
- Adafruit DHT (v1.4.7): For precise environmental sensing.
- PubSubClient (v2.8.0): For reliable MQTT synchronization.
Edge nodes should publish telemetry to the sensors/[device_id]/data topic using the following JSON structure:
{
"device_id": "velesync-node-01",
"temperature": 24.5,
"humidity": 45.2,
"light": 320,
"timestamp": 1715526000
}Velesync utilizes a custom design system focused on Visual Depth and Information Hierarchy:
- Deep Obsidian Base:
#0B0E14provides a high-contrast, professional background. - Electric Cobalt Accents:
#2E5BFFguides the user's eye to critical system updates. - Backdrop Fusion:
backdrop-filter: blur(20px)combined with subtle 1px white borders (8% opacity) creates a premium glass-panel effect. - Neural Gradients: Real-time charts utilize multi-stop CSS gradients to visualize data trends with high fidelity.
Velesync — Synchronizing the Future of IoT.