# UnitV2

## Description

UnitV2 is a high-efficiency AI recognition module launched by M5Stack, using Sigmstar SSD202D (integrated dual-core Cortex-A7 1.2Ghz processor) control core, integrated 256MB-DDR3 memory, 512MB NAND Flash, and 1080P camera. With embedded Linux operating system and rich software and hardware resources and development tools integrated, UnitV2 is committed to bringing users a simple and efficient AI development experience out of the box.

## Out Of The Box AI Recognition Function

- UnitV2 integrates not only the basic AI recognition service developed by M5Stack, but also has built-in multiple recognition functions (such as face recognition, object tracking and other common functions), which can quickly help users build AI recognition applications.
- All features! Plug and play! UnitV2 has a built-in wired network card. When you connect to a PC through the TypeC interface, it will automatically establish a network connection with UnitV2. With highly free connectable style, it can also be connected and debugged via WiFi.
- UART serial port output, all identification content is automatically output in `JSON` format through the serial port, which is convenient to call.

## Development Efficiency Improvement

- UnitV2's factory Linux image integrates a variety of basic peripherals and development tools (such as Jupter Notebook etc.)
- Through SSH access, you can fully control the hardware resources of this camera
- Easily build a custom recognition model through M5Stack's V-Training (AI model training service).

## Software Support

- The M5Stack team will update more identification function services through the release of firmware in the future, and users can directly update the software through TFCard.

## Product Features

- Sigmstar SSD202D
- Dual Cortex-A7 1.2Ghz Processor
- 256MB DDR3
- 512MB NAND Flash
- GC2145 1080P Colored Sensor 
- Microphone
- WiFi 2.4GHz

## Include

- 1x UnitV2

## Applications

- AI recognition function development
- Industrial visual identification sorting
- Machine vision learning

## Specification

<table>
    <thead>
    <tr>
        <th>Resources</th>
        <th>Parameter</th>
    </tr>
    </thead>
   <tr>
      <td>Sigmstar SSD202D</td>
      <td>Dual Cortex-A7 1.2Ghz Processor</td>
   </tr>
   <tr>
      <td>Flash</td>
      <td>512MB NAND</td>
   </tr>
   <tr>
      <td>RAM</td>
      <td>256MB-DDR3</td>
   </tr>
   <tr>
      <td>Camera</td>
      <td>GC2145 1080P Colored Sensor </td>
   </tr>
   <tr>
      <td>Lens</td>
      <td>FOV 68° , DOF= 60cm- ∞</td>
   </tr>
   <tr>
      <td>Power Input</td>
      <td>5V @ 500mA</td>
   </tr>
   <tr>
      <td>Peripherals</td>
      <td>TypeC x1, UART x1, TFCard x1, Button x1, Microphone x1, Fan x1</td>
   </tr>
   <tr>
      <td>Indicator light</td>
      <td>Red, While</td>
   </tr>
   <tr>
      <td>WiFi</td>
      <td>150Mbps 2.4GHz 802.11 b/g/n</td>
   </tr>
   <tr>
      <td>Operating Temperature</td>
      <td>32°F to 104°F ( 0°C to 40°C )</td>
   </tr>
   <tr>
      <td>Net weight</td>
      <td>18g</td>
   <tr>
      <td>Gross weight</td>
      <td>62g</td>
   </tr>
   <tr>
      <td>Product Size</td>
      <td>48*18.5*24mm</td>
   </tr>
   <tr>
      <td>Package Size</td>
      <td>157*38*38mm</td>
   </tr>
   <tr>
      <td>Case Material</td>
      <td>Plastic ( PC )</td>
   </tr>
</table>