How to detect mold risk with Home Assistant

Mold thrives in damp, poorly ventilated spaces, and early detection can save you from costly repairs and health issues. Home Assistant, running locally, lets you pull together temperature, humidity, and air‑quality data from a variety of sensors, then turn those readings into actionable warnings. Below is a practical guide to building a mold‑risk monitoring system that stays private, reliable, and easy to expand.

Why mold risk matters and what Home Assistant can do

Mold growth typically begins when relative humidity stays above 60 % for extended periods, especially in cool corners like basements, bathrooms, or behind furniture. By continuously logging temperature and humidity, you can calculate dew point and assess the mold growth index (MGI) – a simple formula that combines RH and temperature to estimate risk. Home Assistant’s local nature means your data never leaves your network, and you can integrate virtually any sensor that speaks MQTT, Zigbee, Z‑Wave, or ESPHome without relying on cloud services.

The real power comes from automations: when conditions cross a threshold, you can trigger notifications, turn on exhaust fans, or even adjust a dehumidifier. Because everything runs on hardware you control – such as a Home Assistant Green or Yellow – you avoid subscription fees and keep the system running even if the internet drops.

Key sensors and placement

Choosing the right sensors is the first step. For basic temperature/humidity monitoring, the Aqara Climate Sensor W100 (/products/aqara-climate-sensor-w100/) is a reliable Zigbee option that reports every few minutes and works well in bedrooms or living rooms. If you prefer a Thread/Matter device, the Eve Room (/products/eve-room/) offers accurate readings plus VOC sensing, which can hint at early mold‑related volatile compounds.

For dedicated air‑quality insight, consider the AirGradient One (/products/airgradient-one/) or the open‑source AirGradient Open Air (/products/airgradient-open-air/). Both measure PM2.5, CO₂, temperature, and humidity, giving you a broader picture of indoor health. Place one near your HVAC return and another in a high‑moisture area like the bathroom.

If you already use HomeKit, the Eve Weather (/products/eve-weather/) can sit outdoors to compare indoor/outdoor conditions, helping you decide when to ventilate. For Z‑Wave networks, the Zooz ZSE44 Temp Humidity Sensor (/products/zooz-zse44-temp-humidity-sensor/) is a rugged choice for basements or crawlspaces.

When positioning sensors, avoid direct sunlight, drafts from vents, or placement behind furniture. Aim for breathing height (about 1 m) in the center of the room, and keep them at least 30 cm away from walls to capture true ambient conditions. In multi‑story homes, place at least one sensor per floor and one in each bathroom.

Automations and alerts

Once sensors are feeding data into Home Assistant, create a template sensor that computes the mold risk index:

template:
  - sensor:
    - name: "Bathroom Mold Risk"
      unit_of_measurement: "%"
      state: >-
        {{ ((states('sensor.bathroom_humidity') | float) - 60) * 2 }}

This simple example subtracts the 60 % baseline and scales the result; you can replace it with a more sophisticated MGI formula if desired. Next, set up an automation that fires when the index exceeds a safe level:

• Trigger: Numeric state of sensor.bathroom_mold_risk above 30 for 10 minutes.
• Action:
  1. Send a persistent notification to your phone.
  2. Turn on a bathroom exhaust fan (e.g., via a [Shelly Plus 1 Mini Gen3](/products/shelly-plus-1-mini-gen3/) /products/shelly-plus-1-mini-gen3/).
  3. If you have a dehumidifier plugged into a smart plug, switch it on (e.g., Zooz Zen05 Outdoor Plug /products/zooz-zen05-outdoor-plug/).

Add a second automation to reset the fan/dehumidifier when humidity drops below 50 % for 15 minutes, preventing over‑drying and saving energy.

For a more polished dashboard, add a gauge card showing the mold risk percentage and a history graph of temperature/humidity. You can also include a “ventilation recommended” button that manually triggers the exhaust fan for 20 minutes.

Quick verdict

Detecting mold risk with Home Assistant is straightforward, inexpensive, and fully local. By deploying a handful of trusted sensors – such as the Aqara Climate Sensor W100, Eve Room, or Airgradient One – and linking them to simple automations, you get real‑time warnings that let you act before mold takes hold. The system respects your privacy, works offline, and can grow with your smart‑home ambitions. If you want a healthy home without relying on third‑party clouds, this approach delivers both early warnings and practical control.