Akida™ Edge AI Box

Overview

Developed in collaboration between VVDN and BrainChip, the Akida™ Edge AI Box is a small form factor device designed to accelerate AI processing and enable advanced AI solutions at the Edge. With the integration of two BrainChip AKD1000 AI Accelerators and NXP's i.MX 8M Plus SoC, this box can execute diverse AI applications for vision, voice, vibration, and many other sensor applications. By processing data close to the sensor, security and privacy are enhanced through minimizing the need for cloud connectivity and reducing exposure of sensitive data.

VVDN and BrainChip also offer customization options to meet specific end-customer requirements.

Highlights

NXP i.MX 8M Plus Quad SoC
2 x BrainChip AKD1000 Processors
4GB LPDDR4, 32GB eMMC
Supports Linux Embedded OS Version 6.1
Small and Compact Size Enclosure
Easy to Build, Deploy, and Manage AI at the Edge
Supports 12VDC with an External Power Adapter

Technical Specifications

Host CPU	NXP i.MX 8M Plus Quad SOC
AI/ML Accelerator	2 x AKD1000 (BrainChip Akida Chip) Over PCIe
Memory	4GB LPDDR4, 32GB eMMC
OS	Linux Embedded OS Version 6.1
External Storage	Micro SD Card Connector that Supports Micro SD
Display	1 x HDMI Output with Max Resolutions of 3840 x 2160p30 Pixel Clock upto 297MHZ
Network Connectivity	Wi-Fi Connectivity: 802.11 ac/b/g/n/c (2.4GHz /5GHz) Ethernet Connectivity: Two Ethernet Port with 10/100/1000 Mbps Ethernet Port Spports External Camera Interface
Max Encode	1 x 1080P60 (H265 & H264) / 2 x 1080P30 (H265 & H264) / 4 x 720P30 (H265 & H264)
Max Decode	1 x 1080P60 (H265 & H264) / 2 x 1080P30 (H265 & H264) / 4 x 720P30 (H265 & H264)
Interfaces	USB 3.0 Port Type A Port USB 2.0 Port Micro B Port (Flashing and Debug port)
User Indication	2x RGB LED for Status Indication Power ON / OFF Indication LED (Green)
Operating Temperature	0°C to 50°C
Operating Humidity	5% to 95%
Power Input	12VDC
Dimensions	110mm x 110mm x 56mm (L x W x H)
Enclosure	Metal + Plastic Enclosure with Heatsink IP42 Ratings

TARGETED APPLICATIONS

QCS8250 SOM compact size and features make it the best to facilitate a cost-effective and efficient system to which next-gen camera modules can be interfaced for various AI-based applications:

Security & Surveillance

Retail

Smart City

Automotive

Transportation

Industrial

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