A practical guide to building production-ready IoT monitoring systems using Raspberry Pi, Python, and MQTT for real-time sensor data collection.
Why Raspberry Pi for IoT?
The Raspberry Pi has evolved from a hobbyist board to a legitimate edge computing platform. With its quad-core processor, built-in WiFi, and GPIO pins, it's the perfect bridge between sensors and the cloud.
Architecture Overview
Our typical IoT stack looks like this:
- Sensors: Temperature, humidity, soil moisture connected via I2C/SPI
- Edge: Raspberry Pi running Python with Kalman filtering
- Transport: MQTT protocol for lightweight messaging
- Cloud: Flask dashboard with real-time WebSocket updates
- Storage: TimescaleDB for time-series data
Kalman Filtering for Sensor Noise
Raw sensor data is noisy. We apply Kalman filtering to get clean, reliable readings. This is especially critical for agricultural monitoring where decisions are made based on sensor thresholds.
Power Management
For remote deployments, we use solar panels with LiFePO4 batteries. The Pi can be configured to deep sleep between readings, achieving 6+ months of autonomous operation.
Getting Started
Check out our Emathrix IoT Dashboard Pro for a ready-to-deploy monitoring solution, or contact us for custom IoT development.