> ## Documentation Index
> Fetch the complete documentation index at: https://docs.edgeimpulse.com/llms.txt
> Use this file to discover all available pages before exploring further.

# AR/XR factory floor (Unity + Meta Quest 3)

> Run an Edge Impulse FOMO vision model fully on-device inside a Unity XR app on Meta Quest 3 / 3S

This example brings Edge Impulse on-device inference into an immersive **Unity XR** app for the **Meta Quest 3 / 3S** (a headset that runs Android). A virtual conveyor belt carries bottles past an inspection station; an Edge Impulse **FOMO object-detection** model checks each bottle's cap, and a reject arm shoves the failures off the belt so they smash on the floor. It all runs locally on the headset, with no network connection.

Because the Quest runs Android, the same Edge Impulse **C++ library** you would deploy to a phone is compiled to a native plugin and called from Unity through a small P/Invoke bridge: the [Android series](/tutorials/topics/android/android-series) NDK approach, wrapped for the Unity engine.

![The conveyor inspection demo](https://raw.githubusercontent.com/edgeimpulse/Unity-ARXR-Factory-Floor-Example/main/docs/media/factory-demo.gif)

<CardGroup cols={2}>
  <Card title="Example repository" icon="github" href="https://github.com/edgeimpulse/Unity-ARXR-Factory-Floor-Example">
    Unity project, native plugin sources and a prebuilt APK.
  </Card>

  <Card title="Public Edge Impulse project" icon="cube" href="https://studio.edgeimpulse.com/public/751472/live">
    Clone the bottle-cap FOMO model into your own account.
  </Card>
</CardGroup>

## What you'll learn

* How to run an Edge Impulse **FOMO** model on-device from **Unity** through a native plugin (no cloud calls).
* How the same Android C++ SDK deployment powers a Meta Quest XR experience.
* How to feed pixels from a Unity camera into the model and act on the result in the scene.

## How it works

A virtual "inspection camera" in Unity renders the bottle at the inspection point, hands the pixels to the Edge Impulse model, and reacts to the result.

<Steps>
  <Step title="Deploy the model as a C++ library">
    In Edge Impulse Studio, go to **Deployment → C++ library** and build. A thin wrapper (`native/ei_fomo.cpp`) exposes a `classify` entry point.
  </Step>

  <Step title="Compile a native plugin per platform">
    Build the wrapper to `libei_fomo.so` (Android `arm64-v8a`, for the Quest) and `libei_fomo.dylib` (macOS, for the Editor). Prebuilt libraries are committed in the repository.
  </Step>

  <Step title="Run inference from Unity">
    `EdgeImpulseFOMO.cs` P/Invokes the plugin; the inspection station classifies each bottle's cap and flags `cap_incorrect` as a defect.
  </Step>

  <Step title="React in the scene">
    Defective bottles are pushed off the conveyor by a reject arm and shatter on impact, while `cap_correct` bottles pass through.
  </Step>
</Steps>

## Requirements

* **Unity 6000.0.32f1**
* A Meta **Quest 3 / 3S** in developer mode (or an arm64 Android device)
* Packages (already in the project): URP, XR Interaction Toolkit, OpenXR, XR Hands
* To rebuild the native library from your own model: the Android **NDK r23b**

## Quick start

Download the latest APK from the repository's [Releases](https://github.com/edgeimpulse/Unity-ARXR-Factory-Floor-Example/releases) page and sideload it onto a Quest 3 / 3S (or an arm64 Android device):

```bash theme={"system"}
adb install -r FactoryFloorXR-latest.apk
```

Or open the project in Unity, open `Assets/Scenes/FactoryFloorDemo.unity`, and press **Play** to run it in the XR Device Simulator. A single `FactoryDemo Bootstrap` object builds the whole scene in code, including the conveyor, inspection station, reject arm, and HUD, so it is easy to read and adapt.

<Tip>
  The experience is designed to be hardware-agnostic: the same Android build runs on a Quest headset for room-scale XR, and the project can be built for a phone or the browser. This is handy for classroom demos, teaching, and events.
</Tip>

## Related

<CardGroup cols={2}>
  <Card title="Android series" icon="android" href="/tutorials/topics/android/android-series">
    The NDK + C++ SDK deployment path this example builds on.
  </Card>

  <Card title="ExecuTorch" icon="fire" href="/tutorials/integrations/executorch">
    Deploy PyTorch models to Android with ExecuTorch and Edge Impulse.
  </Card>
</CardGroup>