RISC computer-on-module RISC-V

USB 3.0USB 2.0WiFi

Product Introduction
The AI SoC Module is a high-performance, power-efficient computing module designed for next‑generation embedded edge vision. Based on the open RISC‑V architecture and a hardware AI acceleration engine, it delivers rapid prototyping and driver-free UVC camera functionality to accelerate deployment in smart security, industrial inspection and IoT edge devices.

Key Advantages

• Rapid deployment & easy integration: from unboxing to running vision inference in under 30 minutes. Streamlined tools and UVC plug-and-play make the module appear as a universal USB camera, shortening prototyping and development cycles by up to 69%.
• Cost-efficient platform: optimized performance-per-dollar to lower system hardware costs by ~30%. Native compatibility with mainstream AI frameworks and OS environments preserves software investments and speeds time-to-market.
• Adaptable edge performance: engineered for diverse domains (industrial automation, smart retail, security, smart home). High-efficiency H.264/H.265 codecs support smooth, low-latency streaming and flexible connectivity (dual-band Wi‑Fi and Ethernet).
• Design & development flexibility: supports a wide camera ecosystem via MIPI and DVP interfaces. Integrated NPU/AI engine runs object detection, classification, face recognition and motion-tracking models on the edge.

Technical Specifications (table)
Feature — Specification
Core Architecture — High-performance RISC-V processor
AI Acceleration — Hardware-integrated NPU / AI engine
Supported Algorithms — Object detection, face recognition, motion tracking, etc.
Camera Interfaces — 1x MIPI CSI, 1x DVP (Digital Video Port)
Video Codec — H.264 / H.265 (low latency)
Connectivity — Dual-band Wi‑Fi (2.4G/5G) + 10/100M Ethernet
USB Function — USB 2.0/3.0 with UVC (driver-free)
OS Support — Linux, RTOS and mainstream AI development environments
Applications — Smart home, industrial QC, security, robotics and other IoT edge deployments (8+ fields)

Features / Technical specifications

• Core Architecture: high-performance RISC-V processor
• AI Acceleration: hardware-integrated NPU / AI engine for on-edge inference
• Supported Algorithms: object detection, face recognition, motion tracking and similar vision AI tasks
• Camera Interfaces: 1x MIPI CSI and 1x DVP supported
• Video Codec Support: H.264 and H.265 optimized for low-latency streaming
• Connectivity: dual-band Wi‑Fi (2.4G/5G) and 10/100M Ethernet
• USB Capability: USB 2.0/3.0 with UVC driver-free functionality (acts as universal USB camera)
• OS & Ecosystem: compatible with Linux, RTOS and mainstream AI frameworks and SDKs
• Key Benefits: rapid prototyping (inference in under 30 minutes), up to 69% reduced development cycles, ~30% system hardware cost reduction
• Typical Applications: embedded vision for smart security, industrial inspection, smart retail, smart home automation, robotics and other IoT edge deployments