
Description

8-Core High-Performance Processor
Powered by the Rockchip RK3576 processor, the AIoT-3576E features a big.LITTLE architecture with 4x Cortex-A72 and 4x Cortex-A53 cores on an 8nm process, reaching up to 2.2GHz.
Paired with the Android 14.0 operating system, it delivers superior energy efficiency and multi-tasking capability—ideal for AI edge computing and high-performance terminal applications.
Multi-OS Compatibility
AIoT-3576E supports multiple operating systems:
- Android 14
- Linux OS
- OpenHarmony
This ensures broad software flexibility and platform security for developers and integrators in enterprise environments.
4K@120Hz Ultra HD Visual Output
The Mali G52 MC3 GPU and integrated image processing algorithms provide:
- Contrast enhancement
- Noise reduction
- Brightness and color optimization
- 4K (3840×2160) decoding at up to 120Hz
Supports:
- LVDS / eDP / DP OUT via Type-C (OTG)
- DP bandwidth: 62 / 2.7 / 5.4 / 8.1 Gbps on 1/2/4 lanes
- Dual-display output with independent screen content
Perfect for AI vision systems, interactive terminals, and AI-powered kiosks.
Rich Expansion Interfaces
AIoT-3576E includes extensive I/O for industrial and AIoT devices:
- 7 x USB ports (Type-C OTG, USB 3.0, USB 2.0, 4x via HUB)
- 1 x RS485 port
- 6 x Expandable serial ports (4 x TTL, 2 x RS232)
- 1 x CAN port
- 4 x GPIO ports
- 2 x ADC ports
These interfaces provide full support for peripheral devices across multiple industrial and AI scenarios.
Advanced Network Connectivity
- The board supports:
- 10/100/1000M adaptive Ethernet port
- WiFi 6 + Bluetooth 5.0, single antenna
- Built-in PCI-E slot for 4G module
Delivers stable, high-speed, and flexible communication for edge devices in dynamic networking environments.
Android System Customization & API Support
- Android OS customization support
- Complete API reference codes provided
- Enables fast integration of upper-layer apps and UI frameworks tailored for industry-specific applications
Application Scenarios
The AIoT-3576E is ideal for high-performance AI computing on the edge, including:
AI Robots
- Edge AI Cloud Servers
- Smart AIoT Terminals
- Industrial Control Hosts
- Intelligent Access Control Devices
- Multi-modal AI Analytics Systems
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