---
layout: page
title: "Trend Binary Sensor"
description: "Instructions on how to integrate Trend binary sensors into Home Assistant."
date: 2016-09-05 10:00
sidebar: true
comments: false
sharing: true
footer: true
ha_category: Utility
logo: home-assistant.png
ha_release: 0.28
ha_iot_class: "Local Push"
ha_qa_scale: internal
---

The `trend` platform allows you to create sensors which show the trend of
numeric `state` or`state_attributes` from other entities. This sensor requires
at least two updates of the underlying sensor to establish a trend.
Thus it can take some time to show an accurate state. It can be useful
as part of automations, where you want to base an action on a trend.

## {% linkable_title Configuration %}

To enable Trend binary sensors in your installation,
add the following to your `configuration.yaml` file:

```yaml
# Example configuration.yaml entry
binary_sensor:
  - platform: trend
    sensors:
      cpu_speed:
        entity_id: sensor.cpu_speed
```

{% configuration %}
sensors:
  description: List of your sensors.
  required: true
  type: map
  keys:
    entity_id:
      description: The entity that this sensor tracks.
      required: true
      type: string
    attribute:
      description: >
        The attribute of the entity that this sensor tracks.
        If no attribute is specified then the sensor will track the state.
      required: false
      type: string
    device_class:
      description: >
        The [type/class](/components/binary_sensor/) of
        the sensor to set the icon in the frontend.
      required: false
      type: string
    friendly_name:
      description: Name to use in the Frontend.
      required: false
      type: string
    invert:
      description: >
        Invert the result. A `true` value would
        mean descending rather than ascending.
      required: false
      type: boolean
      default: false
    max_samples:
      description: Limit the maximum number of stored samples.
      required: false
      type: integer
      default: 2
    min_gradient:
      description: >
        The minimum rate at which the observed value
        must be changing for this sensor to switch on.
        The gradient is measured in sensor units per second.
      required: false
      type: string
      default: 0.0
    sample_duration:
      description: >
        The duration **in seconds** to store samples for.
        Samples older than this value will be discarded.
      required: false
      type: integer
      default: 0
{% endconfiguration %}

## {% linkable_title Using Multiple Samples %}

If the optional `sample_duration` and `max_samples` parameters are specified
then multiple samples can be stored and used to detect long-term trends.

Each time the state changes, a new sample is stored along with the sample time.
Samples older than `sample_duration` seconds will be discarded.

A trend line is then fitted to the available samples, and the gradient of this
line is compared to `min_gradient` to determine the state of the trend sensor.
The gradient is measured in sensor units per second - so if you want to know
when the temperature is falling by 2 degrees per hour,
use a gradient of (-2) / (60 x 60) = -0.00055

The current number of stored samples is displayed on the States page.

## {% linkable_title Examples %}

In this section you find some real-life examples of how to use this sensor.

This example indicates `true` if the sun is still rising:

```yaml
binary_sensor:
  - platform: trend
    sensors:
      sun_rising:
        entity_id: sun.sun
        attribute: elevation
```

This example creates two sensors to indicate whether the temperature is
rising or falling at a rate of at least 3 degrees an hour,
and collects samples over a two hour period:

```yaml
binary_sensor:
  - platform: trend
    sensors:
      temp_falling:
        entity_id: sensor.outside_temperature
        sample_duration: 7200
        min_gradient: -0.0008
        device_class: cold

      temp_rising:
        entity_id: sensor.outside_temperature
        sample_duration: 7200
        min_gradient: 0.0008
        device_class: heat
```
