> For the complete documentation index, see [llms.txt](https://docs.sentiance.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sentiance.com/getting-started/features-catalog/mobility-insights.md).

# Mobility Insights

## Introduction to Mobility Insights

<div><figure><img src="/files/WcIzj5f9NdgPbVvu4NBw" alt=""><figcaption></figcaption></figure> <figure><img src="/files/IcxBCvkCPlxkYRpyiLPM" alt=""><figcaption></figcaption></figure> <figure><img src="/files/5PGYr30K2c47yuiQRvWL" alt=""><figcaption></figcaption></figure></div>

Our platform can help you understand how your users move around and travel using different modes of transportation. We can provide details about their mobility patterns, which means we can track how they go from one place to another, whether they use a car, bicycle, train, etc.

Mobility insights are derived from location and sensor data. This data is processed by ML models to identify the transport modes used during a trip from location A to location B.

A single trip may consist of multiple segments for example, biking to a train station, taking the train, and then a bus to the final destination. Each segment includes distance, duration, and additional contextual details, which together form the complete trip overview.

## Features Overview

{% stepper %}
{% step %}

#### **Transport Mode Detection**

Identifies the mode(s) of transport used during a trip. Multiple modes can be detected within a single journey, see below for a list of our official supported transport modes

* Walking
* Running
* Bicycle
* Motorcycle
* Car
* Bus
* Tram
* Metro
* Train
* Idle
  {% endstep %}

{% step %}

#### **Modal Split**

Aggregates total distance, duration, and number of trips per transport mode. This provides a clear overview of the user’s mobility patterns and insights into their preferred mode of transport
{% endstep %}

{% step %}

#### **Event Timeline**

Mobility Insights can detect when a user starts moving and when they become stationary. These events can be captured and made available in your application either in real time or retrieved on demand.

* **Transport Event**\
  Represents a moment when the user was in movement
* **Stationary Event**\
  Represents a moment when the user was not in movement or stopped moving
* **Off The Grid Event**\
  Represents a moment when the users movement status could not be determined due to different reasons:
  * Airplane mode was turned on
  * GPS or Sensors were not available
  * External system related reason
    {% endstep %}
    {% endstepper %}