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Docker container for the DHT11/DHT22/AM2302 sensors, able to relay sensor readings to a MQTT broker. Integrates with HomeAssistants' discovery protocol and incorporates a robust outlier detection scheme. All features are configurable, where the container can be used to simply log data too.

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hvalev/dht22mqtt-homeassistant-docker

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dht22 temperature/humidity sensor in a docker container

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This docker container enables you to use the DHT11, DHT22 or AM2302 temperature and humidity sensors on a GPIO enabled device such as raspberry pi. The container features a robust scheme to detect outliers and filter data in real-time. Additionally, this container can communicate with an MQTT broker and relay the sensors' values and integrates with home assistants' discovery protocol. Discovery will automatically detect the sensor and make it available for visualizations, automations, etc.

How to run it

The following docker run command or docker-compose service will get you up and running with the minimal configuration.

docker run --device=/dev/gpiomem:/dev/gpiomem -e topic=zigbee2mqtt -e device_id=dht22 -e broker=192.168.X.X -e pin=4 hvalev/dht22mqtt-homeassistant
version: "3.8"
services:
  dht22mqtt:
    image: hvalev/dht22mqtt-homeassistant
    container_name: dht22mqtt
    devices:
      - /dev/gpiomem:/dev/gpiomem
    environment:
      - topic=zigbee2mqtt
      - device_id=dht22
      - broker=192.168.X.X
      - pin=4

/dev/gpiomem:/dev/gpiomem is required to access the GPIO and communicate with your DHT22 sensor. If it doesn't work, you can try to run the container in privileged mode privileged:true.

Parameters

The container offers the following configurable environment variables:

Parameter Possible values Description Default
topic MQTT topic to submit to. zigbee2mqtt
device_id Unique identifier for the device. If you have multiple, you could use something like bedroom_dht22. dht22
broker MQTT broker ip address. 192.168.1.10
username MQTT username. None
password MQTT password. None
pin GPIO data pin your sensor is hooked up to. 4
poll Sampling rate in seconds. Recommended is the range between 2 to 30 seconds. Further information: DHT11/DHT22/AM2302 spec sheet. 2
device_type dht11 or dht22 Sensor type. dht22 also also works for AM2302 dht22
unit C or F Measurement unit for temperature in Celsius or Fahrenheit. C
mqtt_chatter essential|ha|full Controls how much information is relayed over to the MQTT broker. Possible non-mutually exclusive values are: essential - enables basic MQTT communications required to connect and transmit data to the zigbee broker; ha enables home assistant discovery protocol; full enables sending information about the outlier detection algorithm internals over to the MQTT broker. essential|ha
logging log2stdout|log2file Logging strategy. Possible non-mutually exclusive values are: log2stdout - forwards logs to stdout, inspectable through docker logs dht22mqtt and log2file which logs temperature and humidity readings to files timestamped at containers' start. none
filtering enabled or none Enables outlier filtering. Disabling this setting will transmit the raw temperature and humidity values to MQTT and(or) the log. enabled

If you end up using log2file, make sure to add this volume in your docker run or docker-compose commands - ~/yourfolderpath:/log to be able to access the logs from your host os.

If you want to run this container to simply record values to files with no MQTT integration, you need to explicitly set mqtt_chatter to a blank string. In that case, you can also omit all MQTT related parameters from your docker run or compose configurations.

If you're using this container for multiple sensors on the same or different devices which, however, connect to the same mqtt network, you need to explicitly pick a unique device_id for each. Otherwise, identically named devices will boot each other off the network each time they transmit a reading.

Connecting your sensor

To connect your sensor you can look at the following pinout. Typically each sensor needs to be connected to a power, ground and data pin. The data pin needs to be indicated in the pin parameter in order to read the sensor readings.

Raspberry-Pi-GPIO-Header.png
Image Source. A depiction of the Raspberry Pi GPIO pin header. pin is the number following the GPIO label.

Outlier detection scheme

To detect outliers, I'm using the 68–95–99.7 rule, where a reading is considered to be an outlier when it lies beyond 3 standard deviations from the mean. In order to have a scheme, which is adaptive to rapid changes, I'm using two FILO stacks which store the last 10 valid readings for temperature and humidity respectively. When receiving a new reading, a mean and standard deviation are computed for the values in the stack and then subsequently used to detect whether this new reading is valid or an outlier. This allows the algorithm to adapt to gradual changes in sensor readings. Valid readings are added to the stack only if they are unique to the elements contained in the stack. This is done to prevent the stack from homogenizing and ensures that the standard deviation will never be 0.

A weakness in the design is the initiation phase, when the stack is not fully populated or when multiple consecutive readings are outliers. To remedy this, the algorithm keeps track of successive outlier detections and flushes the stack when 3 such readings are detected. This prevents the stack from fitting on outliers if we presume that we get abnormal values less than half the time. Then again, perhaps the temperature really is 97°C.

Most of the time, outliers for temperature and humidity occur simultaneously. As such a conservative approach is implemented, where only non-outliers for both temperature and humidity and forwarded. The following plots depict the temperature and humidity values at different sampling rates, where the first plot represents the original data and subsequent ones - simulating sparser sampling frequencies. The black vertical lines signify when the stack has been flushed.

temperature.png humidity.png
Temperature Humidity

Visualize your own data

If you'd like visualize and check your own data (provided you have used the -logging=log2file option) to perhaps tweak the sampling rate (or stack size, if you're building it yourself), you can take a look at the dht22mqtt_visualize.py script. As long as you change the filename to your own, it will plot your data at the original sampling rate and simulate sparser ones for comparison.

Acknowledgements

The following resources have been very helpful in getting this project up and running:
https://github.com/jumajumo/dht22-docker-arm/blob/master/publish.py
https://forum.dexterindustries.com/t/solved-dht-sensor-occasionally-returning-spurious-values/2939/5

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Docker container for the DHT11/DHT22/AM2302 sensors, able to relay sensor readings to a MQTT broker. Integrates with HomeAssistants' discovery protocol and incorporates a robust outlier detection scheme. All features are configurable, where the container can be used to simply log data too.

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