# Intro

## Who this documentation is for

The following documentation is for TNC staff who are actively scaling and managing wireless camera trap networks and using [Animl](https://animl.camera) for data processing, and for anyone interested in replicating similar systems elsewhere!

The system we use integrates [locally-networked, radio-based camera traps](/fundamentals/types-of-wireless-camera-traps.md#locally-networked-radio-based-camera-traps) (Buckeye X80s) and cellular camera traps ([RidgeTec Lookout 4G LTEs](https://www.trailcampro.com/products/ridgetec-lookout-4g-lte)) with [Animl](https://animl.camera), a software platform we've developed for managing camera trap data and performing machine learning inference in the cloud.

<figure><img src="/files/TF7aSUWwP4NRltx3RdXR" alt=""><figcaption><p>Diagram of how The Nature Conservancy's invasive species monitoring cameras work on Santa Cruz Island</p></figcaption></figure>

This documentation is meant to supplement the existing product documentation published by the camera manufacturers, provide specific guidance for integrating these types of cameras with Animl, and share lessons-learned/best practices for long-term deployments in the field.

{% hint style="info" %}
**Access to Animl**

If you're interested in using Animl for data processing and managment for your project, please reach out to Nathaniel Rindlaub at \<first name>.\<last name>@tnc.org
{% endhint %}


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