# Zones

Zones serve to compartmentalise offices, whether by departments, teams, facilities, or any other preferred criteria. This aids users in accessing real-time data within those designated areas. 

Additionally, in the future, it will enable you to locate available desks and meeting spaces within specific zones. 

{% hint style="info" %}
It's important to note that zones are considered as non-bookable resources and do not require prior creation in Office 365 or Google Workspace.
{% endhint %}

For instance, if you were to integrate a people-counting sensor in a zone and make that data accessible through our web and mobile application, it would provide valuable insights for office occupants to gauge the level of activity in specific areas.

Furthermore, consider the scenario of incorporating an environmental sensor in an open workspace. By analysing this data, you can gain insights into the environmental conditions of various parts of your office. 

This not only empowers users to choose their workspace based on air quality and temperature information but also contributes to understanding the overall health of your building.

![](https://help.meetuma.ai/rest/api/content/988315666/child/attachment/att994017285/download)

Once your zone has been created you can assign it an area of your office on the map.

![](https://help.meetuma.ai/rest/api/content/988315666/child/attachment/att994181123/download)

Once you've assigned the zone, you can click on **zone view** to see all the zones you've assigned to the map. If you hover over a zone it will initially tell you it has no data to show.

To start visualising data, add an IoT sensor to a zone.

Once you've added one of these devices to a Zone, navigate back to the map and you should see your data start to show.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://support.meetuma.ai/uma-knowledgebase/user-guides/zones.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.