HomematicIP + MQTT
HomematicIP room thermostats (living room, bedroom, home office) report temperature and humidity into the smart home dashboard via a small, deliberately low-tech bridge: Home Assistant → MQTT → InfluxDB.
Why this path, and not a direct integration
A dedicated HomematicIP-to-MQTT exporter used to run as a standalone Docker container, but the underlying Python library lost compatibility with HomematicIP's cloud API and hasn't been maintained since 2022. Home Assistant, on the other hand, ships an actively maintained HomematicIP Cloud integration — so instead of chasing a broken exporter, the bridge now runs as native Home Assistant automations that simply republish sensor state changes to MQTT.
How it works
- Home Assistant automations trigger on thermostat state changes.
- Each automation publishes the current temperature and humidity to a per-room MQTT topic.
- A small .NET background service subscribes to those topics and writes the values into InfluxDB, tagged by room and sensor type.
- Grafana reads from InfluxDB for the temperature/humidity dashboards.
The Home Assistant automations
Each room has its own automation in Home Assistant that listens for
state changes on the corresponding HomematicIP thermostat entity. When
the temperature or humidity changes, the automation publishes the new
values to MQTT topics like homematic/livingroom/temperature
and homematic/livingroom/humidity. The automations are
simple YAML configurations, not custom code, which makes them easy to
maintain and debug.
The InfluxDB writer
A small .NET background service runs as a Docker container and
subscribes to all homematic/+/+ MQTT topics. When a
message arrives, it parses the room name and measurement type from the
topic, converts the value to a float, and writes it into InfluxDB with
appropriate tags. The service handles connection drops and reconnection
automatically, and logs all write operations for debugging.
Dashboard integration
Grafana queries InfluxDB using Flux to display real-time temperature and humidity charts for each room. The dashboards show current values, 24-hour trends, and historical averages. This data is also used in the home dashboard to display room temperatures alongside other sensor data like air quality and power consumption.
Why this is worth documenting
- No extra Docker container or unmaintained library dependency.
- Cloud-API changes are absorbed by Home Assistant's own maintainers, not by custom code.
- The MQTT bridge is just configuration (automations), not a service that needs its own uptime monitoring.
- The entire chain is observable: MQTT topics can be monitored with any MQTT client, InfluxDB has its own explorer, and Grafana dashboards show the data flow end-to-end.
Lessons learned
The original approach of running a dedicated exporter was more "architecturally pure" but fragile in practice. When the Python library stopped working, the entire sensor pipeline broke. The Home Assistant approach is more robust because it leverages a well-maintained integration and uses MQTT as a simple, well-understood transport layer. The lesson: for home automation, prefer integrations that are actively maintained over custom code that needs constant attention.