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+---
+layout: page
+title: "Bayesian Binary Sensor"
+description: "Instructions how to integrate threshold Bayesian sensors into Home Assistant."
+date: 2017-08-27 20:05
+sidebar: true
+comments: false
+sharing: true
+footer: true
+logo: home-assistant.png
+ha_category: Binary Sensor
+ha_iot_class: "Local Polling"
+ha_release: 0.53
+---
+
+
+The `bayesian` binary sensor platform observes the state from multiple sensors
+and uses Bayes' rule to estimate the probability that an event has occurred
+given the state of the observed sensors. If the estimated posterior probability
+is above the `probabiliy_threshold`, the value of the sensor is `on`.
+Otherwise, the sensor is `off`.
+
+This allows for the detection of complex events that may not be readily
+observable, i.e. cooking, showering, in bed, start of morning routine, etc.  It
+can also be used to gain greater confidence about events that _are_ directly
+observable, but for which the sensors can be unreliable, i.e. presence.
+
+To enable the Bayesian sensor, add the following lines to your `configuration.yaml`:
+
+```yaml
+# Example configuration.yaml entry
+binary_sensor:
+  name: 'currently_cooking'
+  platform: 'bayesian'
+  prior: 0.1
+  probability_threshold: 0.7
+  observations:
+    - entity_id: 'switch.kitchen_lights'
+      prob_given_true: 0.6
+      prob_given_false: 0.2
+      platform: 'state'
+      to_state: 'on'
+    - entity_id: 'sensor.stove_temperature'
+      prob_given_true: 0.9
+      platform: 'numeric_state'
+      above: 100
+    - entity_id: 'sensor.kitchen_motion'
+      prob_given_true: 0.5
+      prob_given_false: 0.2
+      platform: 'state'
+      to_state: 'on'
+
+binary_sensor:
+  name: 'in_bed'
+  platform: 'bayesian'
+  prior: 0.25
+  probability_threshold: 0.95
+  observations:
+    - entity_id: 'sensor.living_room_motion'
+      prob_given_true: 0.4
+      prob_given_false: 0.2
+      platform: 'state'
+      to_state: 'off'
+    - entity_id: 'sensor.basement_motion'
+      prob_given_true: 0.5
+      prob_given_false: 0.4
+      platform: 'state'
+      to_state: 'off'
+    - entity_id: 'sensor.bedroom_motion'
+      prob_given_true: 0.5
+      platform: 'state'
+      to_state: 'on'
+    - entity_id: 'sensor.sun'
+      prob_given_true: 0.7
+      platform: 'state'
+      to_state: 'below_horizon'
+```
+
+Configuration variables:
+- **prior** (*Required*): The prior probability of the event.  At any point in
+time (ignoring all external influences) how likely is this event to occur?
+- **observations** (*Required*): The observations which should influence the
+likelihood that the given event has occurred. The only supported observation
+platforms are `state` and `numeric_state`, which are modeled after their
+corresponding triggers for automations.  In addition to the automation syntax,
+the observations also require `prob_given_true` (the probability of the
+observation occurring, given the event is true).  The optional
+`prob_given_false` (the probability of the observation occurring, given the
+event is false) can be set as well.  If `prob_given_false` is not set, it will
+default to `1 - prob_given_true`.
+- **probability_threshold** (*Optional*): The probability at which the sensor
+should trigger to `on`.
+- **name** (*Optional*): Name of the sensor to use in the frontend. Defaults to
+`Bayesian Binary`.
+