Foxconn, Socionext and Hailo collaborate for edge video analytics
Smart manufacturing specialist, Foxconn, video and imaging SoC company, Socionext and artificial intelligence (AI) chip manufacturer, Hailo, have partnered to introduce Boxiedge AI edge computing for energy-efficient, standalone, AI inference nodes.
Foxconn’s high-density, fanless Boxiedge edge computer is combined with Socionext’s SynQuacer SC2A11, high-efficiency parallel processor and the Hailo-8 deep learning processor. According to the trio, the combination provides market-leading energy efficiency for standalone AI inference nodes, in smart cities, smart medical, smart retail applications and the industrial IoT.
It is designed to address the need for cost-effective multi-processing capabilities required in video analytics, image classifications and object segmentation in these compute-intensive applications. The robust, Boxiedge AI edge computing product is capable of processing and analysing over 20 streaming camera input feeds in real-time, at the edge. The result is a high-density, low-power, local video management system (VMS) server, ensuring top performance for video analytics and privacy, including image classification, detection, pose estimation, and various other AI-powered applications – all in real time.
Hailo’s specialised Hailo-8 deep learning processor features up to 26 Tera operations per second (TOPS). Its architecture enables edge devices to run sophisticated deep learning applications that could previously only run on the cloud. Its structure translates into higher performance, lower power and minimal latency, enabling enhanced privacy and better reliability for smart devices operating at the edge, said the company.
Gene Liu, VP of semiconductor sub group at Foxconn Technology, said: “We recognise the great potential in adopting AI solutions for a multitude of applications, such as tumor detection and robotic navigation. . . our edge computing solution combined with Hailo’s deep learning processor will create even better energy efficiency for standalone AI inference nodes to positively impact rapidly evolving [market] sectors.”
“We are very pleased with this joint effort by the companies, and to officially announce our strategic partnership with Hailo,” said Noriaki Kubo, executive VP at Socionext. “This collaboration will lead to more innovative solutions that specifically address the growing demand from our AI customers in multiple sectors. We are confident that this product will enable endpoint devices to operate with better performance, lower power, more flexibility, and minimal latency.”
The next generation of the Boxiedge AI computing is equipped with applications for a broader market relying on low latency, a high data rate, high reliability and quick processing at the edge. Smart retail and smart cities, for instance, require hundreds of cameras – either in-store or in traffic monitoring – to generate video streams that need to be processed locally, quickly, and efficiently with minimal latency.
Similarly, for industrial IoT, data acquiring, processing, inferencing, and presenting on the production floor rather than in the cloud translates into significant cost savings along with more efficient processing for tasks such as inspection and quality assurance.
