hassio-addons/mi-scale

Xiaomi Mi Scale Add On for Home Assistant

Add-On for HomeAssistant to read weight measurements from Xiaomi Body Scales.

BREAKING CHANGE:

Please note there was a breaking change in 0.1.8. The MQTT message json attributes are now in lower snake_case to be compliant with Home-Assistant Attributes. This means Home-Assistant sensor configuration needs to be adjusted. For example value_template: "{{ value_json['Weight'] }}" Needs to be replaced with value_template: "{{ value_json['weight'] }}" (note the lowercase w in weight)

Supported Scales:

Name	Model	Picture
Mi Smart Scale 2	XMTZCO1HM, XMTZC04HM
Mi Body Composition Scale	XMTZC02HM
Mi Body Composition Scale 2	XMTZC05HM

Setup

1. Retrieve the scale's MAC Address from the Xiaomi Mi Fit App:

2. Open Home Assistant and navigate to add-on store. Click on the 3 dots (top right) and select Repositories
3. Enter https://github.com/lolouk44/hassio-addons in the box and click on Add
4. You should now see Lolouk44 Add-Ons at the bottom list:
5. Click on Xiaomi Mi Scale then click on Install
6. Edit the Configuration

Option	Type	Required	Description
HCI_DEV	string	No	Bluetooth hci device to use. Defaults to hci0
MISCALE_MAC	string	Yes	Mac address of your scale
MQTT_PREFIX	string	No	MQTT Topic Prefix. Defaults to miscale
MQTT_HOST	string	Yes	MQTT Server (defaults to 127.0.0.1)
MQTT_USERNAME	string	No	Username for MQTT server (comment out if not required)
MQTT_PASSWORD	string	No	Password for MQTT (comment out if not required)
MQTT_PORT	int	No	Defaults to 1883
TIME_INTERVAL	int	No	Time in sec between each query to the scale, to allow other applications to use the Bluetooth module. Defaults to 30
MQTT_DISCOVERY	bool	No	MQTT Discovery for Home Assistant Defaults to true
MQTT_DISCOVERY_PREFIX	string	No	MQTT Discovery Prefix for Home Assistant. Defaults to homeassistant

Auto-gender selection/config -- This is used to create the calculations such as BMI, Water/Bone Mass etc... Up to 3 users possible as long as weights do not overlap!

Here is the logic used to assign a measured weight to a user:

if [measured value in kg] is greater than USER1_GT, assign it to USER1
else if [measured value in kg] is less than USER2_LT, assign it to USER2
else assign it to USER3 (e.g. USER2_LT < [measured value in kg] < USER1_GT)

Option	Type	Required	Description
USER1_GT	int	Yes	If the weight (in kg) is greater than this number, we'll assume that we're weighing User #1
USER1_SEX	string	Yes	male / female
USER1_NAME	string	Yes	Name of the user
USER1_HEIGHT	int	Yes	Height (in cm) of the user
USER1_DOB	string	Yes	DOB (in yyyy-mm-dd format)
USER2_LT	int	No	If the weight (in kg) is less than this number, we'll assume that we're weighing User #2. Defaults to USER1_GT Value
USER2_SEX	string	No	male / female. Defaults to female
USER2_NAME	string	No	Name of the user. Defaults to Serena
USER2_HEIGHT	int	No	Height (in cm) of the user. Defaults to 95
USER2_DOB	string	No	DOB (in yyyy-mm-dd format). Defaults to 1990-01-01
USER3_SEX	string	No	male / female. Defaults to female
USER3_NAME	string	No	Name of the user. Defaults to Missy
USER3_HEIGHT	int	No	Height (in cm) of the user. Defaults to 150
USER3_DOB	string	No	DOB (in yyyy-mm-dd format). Defaults to 1990-01-01

7. Start the add-on

Home-Assistant Setup:

Under the sensor block, enter as many blocks as users configured in your environment variables:

  - platform: mqtt
    name: "Example Name Weight"
    state_topic: "miscale/USER_NAME/weight"
    value_template: "{{ value_json['weight'] }}"
    unit_of_measurement: "kg"
    json_attributes_topic: "miscale/USER_NAME/weight"
    icon: mdi:scale-bathroom

  - platform: mqtt
    name: "Example Name BMI"
    state_topic: "miscale/USER_NAME/weight"
    value_template: "{{ value_json['bmi'] }}"
    icon: mdi:human-pregnant
    unit_of_measurement: "kg/m2"

Acknowledgements:

Thanks to @syssi (https://gist.github.com/syssi/4108a54877406dc231d95514e538bde9) and @prototux (https://github.com/wiecosystem/Bluetooth) for their initial code

Special thanks to @ned-kelly for his help turning a "simple" python script into a fully fledged docker container

Thanks to @bpaulin for his PRs and collaboration