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INSIGHTS

Transformative AI processing solution for video analytics at the edge

Transformative AI processing solution for video analytics at the edge
Sensor-enabled technology is at the heart of exciting innovation in the retail, smart city, and industrial sectors. However, processing and analyzing all this data, especially from video sources, remains a significant bottleneck.

First, a few comments on why the future of smart technologies resides at the edge and not in the cloud.

Sensor-enabled technology is at the heart of exciting innovation in the retail, smart city, and industrial sectors. However, processing and analyzing all this data, especially from video sources, remains a significant bottleneck. The traditional cloud server systems in widespread use today cost too much, use too much energy, and take up too much space. 

Further advancements in these and other smart technologies require more affordable and efficient solutions for video processing and analytics – and these systems need to be at the edge. 

Why the edge? Consider emerging applications in smart retail, smart cities, and industrial IoT that utilize a large number of cameras to do things like monitor in-store activity, ensure production quality, or manage urban traffic. For this information to be valuable, it must be processed quickly, efficiently, and with minimal latency, which is not practical in the cloud. Using traditional cloud servers is no longer viable to scale smart applications cost-effectively.

Overcoming this bottleneck is why Socionext, a semiconductor solutions company, introduced the multicore SynQuacer line of SoCs. The SynQuacer SoCs are cost-effective and energy-efficient chips capable of delivering the multiprocessing required for robust AI-powered video analytics at the edge.

Edge video analytics powered by Socionext SynQuacer SC2A11 & Hailo-8

Socionext has teamed up with Hailo, an innovative AI chipmaker, to launch a next-generation processing solution to deliver AI video analytics at the edge. The system combines the Socionext SynQuacer SC2A11 multicore SoC optimized for low-power edge devices with the Hailo-8 deep learning processor. 

The combined edge-based solution is a highly scalable and efficient platform enabling top performance for AI-enhanced video processing and analytics. Foxconn, with its BOXiedge edge computing solution, is one of the first companies to deploy this game-changing technology. 

Socionext SynQuacer SC2A11 

The Socionext SynQuacer SC2A11 incorporates twenty-four ultra-low-power ARM CortexTM-A53 cores operating at 1 GHz while supporting up to 64 GB of DDR4-2133 ECC memory. The device is an ideal foundation for low-cost, highly-integrated, and power-efficient server systems deployed to handle edge computing, Internet of Things (IoT) data processing, and cloud service applications. 

Hailo-8 AI Processor 

 
Measuring at only 15 x 15mm, the small size Hailo-8 AI chip features an innovative architecture capable of performing up to 26 Tera Operations Per Second (TOPS), a level of performance that enables edge devices to run sophisticated deep learning applications that could previously run only on the cloud. The advanced structure of the Hailo-8 translates into higher performance, lower power (< 2W under typical operation), and minimal latency.

Use case example – Foxconn BOXiedge edge server

The Foxconn BOXiedge edge computing solution is one of the first application examples to come out of our collaboration with Hailo Technologies. Under the hood, the BOXiedge device features the SynQuacer SC2A11 high-efficiency parallel processing SoC integrated with a Hailo-8 AI M.2 module. A demonstration of this was featured at CES 2020. Follow the links to view the demo brief and Hailo’s video.

The BOXiedge system, capable of processing and analyzing input from over twenty cameras in real-time, is a cost-effective and scalable smart video management system (VMS) with advanced AI video analytics features.


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