ESPHome sample configuration for an HX711 powered Smart Scale including Auto-Tare functionality.

esphome hx711 bed occupancy sensor for 8 legged bed.yaml

################################################
#                  Secrets
################################################

# Add these to your secrets.yaml (in the top right corner of esphome):
# wifi_ssid: "your_wifi_ssid"
# wifi_password: "your_wifi_password"
# api_key: "your_api_key"
# ota_password: "your_ota_password"

# You can get a randomly generated key for api_key and ota_password from here:
# https://esphome.io/components/api.html

# You can also enter them direcly in here,
# but setting them in secrets.yaml allows you to easily reuse them for other esphome devices

wifi:
  ssid: !secret wifi_ssid
  password: !secret wifi_password

api:
  encryption:
    key: !secret api_key

ota:
  password: !secret ota_password

################################################

esphome:
  name: bed-occupancy
  platform: ESP8266
  board: d1_mini_lite

globals:
  - id: initial_zero
    type: float
    restore_value: yes
    # NOTE: make sure to align this value to the one used in "calibrate_linear" below!
    initial_value: '1822466'
    
  - id: auto_tare_enabled
    type: bool
    restore_value: yes
    initial_value: 'true'

  - id: auto_tare_difference
    type: float
    restore_value: yes
    initial_value: '0'
    
  - id: manual_tare_flag
    type: bool
    restore_value: no
    initial_value: 'false'

# Enable logging
logger:
  level: ERROR

status_led:
  pin:
    number: GPIO2
    inverted: True
    allow_other_uses: true
    
switch:
  ## Switch to enable/disable the auto tare feature
  - platform: template
    id: bed_occupancy_continuous_tare_enabled
    name: "Bed Occupancy Continuous Tare Enabled"
    lambda: |-
      return id(auto_tare_enabled);
    turn_on_action:
      - lambda: |-
          id(auto_tare_enabled) = true;
    turn_off_action:
      - lambda: |-
          id(auto_tare_enabled) = false;
  
  ## Switch used to initiate a manual tare
  - platform: template
    id: bed_occupancy_manual_tare_action_switch
    name: "Bed Occupancy Manual Tare Action"
    lambda: |-
      return id(manual_tare_flag);
    turn_on_action:
      - lambda: |-
          id(auto_tare_difference) = id(initial_zero) - id(bed_occupancy_hx711_value_raw).state;
      - switch.turn_off: bed_occupancy_manual_tare_action_switch
    turn_off_action:
      - lambda: |-
          id(manual_tare_flag) = false;
## Sensor Configuration ##
sensor:
  # template sensors from global variables
  - platform: template
    id: bed_occupancy_initial_zero
    name: "Bed Occupancy Initial Zero"
    lambda: |-
      return id(initial_zero);
    update_interval: 1s
    
  - platform: template
    id: bed_occupancy_auto_tare_difference
    name: "Bed Occupancy Auto Tare Difference"
    lambda: |-
      return id(auto_tare_difference);
    update_interval: 1s
    
  # sensors imported from home assistant
  - platform: homeassistant
    id: homeassistant_initial_zero
    entity_id: input_number.bed_occupancy_initial_zero
    on_value:
      then:
        - lambda: |-
            id(initial_zero) = x;
  
  ################################################
  # RAW Scale input
  ################################################

  #Bed 1 RAW
  - platform: hx711
    name: "bed1"
    id: bed1
    dout_pin: 
      number: D4
      allow_other_uses: true
    clk_pin: D3
    gain: 128
    update_interval: 0.2s
    internal: true

  #Bed 2 RAW  
  - platform: hx711
    name: "bed2"
    id: bed2
    dout_pin: D2
    clk_pin: D1
    gain: 128
    update_interval: 0.2s
    internal: true

  #Summed RAW 
  - platform: template
    id: bed_occupancy_hx711_value_raw
    lambda: |-
      return (id(bed1).state + id(bed2).state);
    internal: True
    unit_of_measurement: kg
    accuracy_decimals: 3
    update_interval: 0.2s
    filters:
      - sliding_window_moving_average:
          window_size: 3
          send_every: 1
    on_value:
      then:
        - sensor.template.publish:
            id: bed_occupancy_hx711_value
            state: !lambda 'return id(bed_occupancy_hx711_value_raw).state;'
        - if:
            condition:
              and:
                - lambda: 'return id(auto_tare_enabled);'
                # current Bed Occupancy value is below approx. 10KG (raw value -275743) aka nobody is standing on the scale
                - lambda: 'return id(bed_occupancy_hx711_value).state < 10.0;'
            then:
              - if:
                  condition:
                    # current raw scale value is below expected zero value
                    - lambda: 'return id(bed_occupancy_hx711_value_raw).state < (id(initial_zero) - id(auto_tare_difference));'
                  then:
                    # INcrease Auto-Tare offset to slowly align real zero value with expected zero value
                    - lambda: |-
                        id(auto_tare_difference) += 10;
                  else:
                    # DEcrease Auto-Tare offset to slowly align real zero value with expected zero value
                    - lambda: |-
                        id(auto_tare_difference) -= 10;
    
  # Mapped value to KG
  - platform: template
    id: bed_occupancy_hx711_value
    name: "Bed Occupancy HX711 Value"
    icon: mdi:scale
    internal: False
    filters:
      # apply auto_tare difference
      - lambda: 'return x + id(auto_tare_difference);'
      # apply rough calibration
      - calibrate_linear:
          # retrieve these values by evaluating the raw values with loads of known mass.
          # note that a bigger difference between measurements usually results in higher resolution,
          # so measure 0 Kg and the highest known mass you have (like f.ex. your own weight, measured by a normal scale with good accuracy)
          - 1822466 -> 0
          - 2095070 -> 40
      # map values below 0.1 to 0 (to decrease value changes due to random fluctuation)
      - lambda: |-
          if (x <= 0.1) {
            return 0.0;
          } else {
            return x;
          }
          
    unit_of_measurement: kg
    accuracy_decimals: 2
    update_interval: 2s
    
binary_sensor:
  - platform: template
    name: "Bed Occupied"
    device_class: occupancy
    icon: mdi:bed-king
    lambda: |-
      if (id(bed_occupancy_hx711_value).state > 20) {
        return true;
      } else {
        return false;
      }      
      
  - platform: template
    name: "Bed Full"
    icon: mdi:bed-king
    lambda: |-
      if (id(bed_occupancy_hx711_value).state > 50) {
        return true;
      } else {
        return false;
      }