Description UnitV2 is a standalone AI camera module for edge computing. It uses the SigmaStar SSD202D control core with an integrated dual-core Cortex-A7 1.2GHz processor, 128MB DDR3 memory, 512MB NAND Flash, and a GC2145 1080P color sensor. UnitV2 runs an embedded Linux operating system and provides rich software and hardware resources for plug-and-play AI recognition development. It is designed to help users quickly build AI vision applications with built-in recognition functions, web preview, WiFi debugging, and UART JSON output. Note: It is recommended to use the original M5 data cable when connecting UnitV2 to a computer, otherwise crashes may occur. Loose data cables may also cause crashes. Edge and Chrome browsers are recommended, as Firefox may cause freezing or unstable video playback. Features SigmaStar SSD202D control core Dual-core Cortex-A7 1.2GHz processor 128MB DDR3 memory 512MB NAND Flash GC2145 1080P color sensor Built-in microphone 2.4GHz WiFi Embedded Linux operating system Built-in AI recognition service UART serial output in JSON format Specifications Specification Parameter Processor SigmaStar SSD202D, dual Cortex-A7 1.2GHz Flash 512MB NAND RAM 128MB DDR3 Camera GC2145 1080P color sensor Lens FOV 68°, DOF = 60cm - ∞ Input Voltage 5V @ 500mA Hardware Peripherals Type-C x1, UART x1, TFCard x1, Button x1, Microphone x1, Fan x1 Indicators Red, White WiFi 150Mbps 2.4GHz 802.11 b/g/n Operating Temperature 0 ~ 60°C Shell Material Plastic (PC) Product Size 48.0 x 18.5 x 24.0mm Product Weight 18.0g Package Size 157.0 x 38.0 x 38.0mm Gross Weight 62.0g Interface USB Type-C interface for power and computer connection UART interface for JSON-format recognition output TF card slot Button Built-in microphone Built-in fan Red and white status indicators Applications AI recognition function development Industrial visual recognition and classification Machine vision learning Face recognition projects Object tracking projects Product List 1 x UnitV2 1 x 32GB microSD Card 1 x USB Type-C Cable (50cm) 1 x Stand 1 x Back Clip Schematics Model Size Software and Development Built-in AI recognition service with multiple recognition functions Supports connection through Type-C with automatic network connection to UnitV2 Supports WiFi connection and debugging Recognition content can be output through UART in JSON format Resources Official Documentation Built-in Recognition Function Tutorial V-Training Online AI Model Training Service Jupyter Notebook Development Tutorial SSH Connection and WiFi Configuration Firmware Update Tutorial UnitV2Framework SDK UnitV2 Model Size PDF FAQ What processor does UnitV2 use? UnitV2 uses the SigmaStar SSD202D with a dual-core Cortex-A7 1.2GHz processor. What camera sensor does it use? It uses a GC2145 1080P color sensor. Does UnitV2 support WiFi? Yes. It supports 2.4GHz WiFi. Can recognition results be output through UART? Yes. Recognition content can be output through UART in JSON format. Which browsers are recommended? Edge and Chrome are recommended. Firefox may cause freezing or unstable video playback. What is included in the package? The package includes UnitV2, a 32GB microSD card, a USB Type-C cable, a stand, and a back clip.
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