Foxconn, Socionext and Hailo have developed an AI-based system for video analytics at the edge, designed for industrial IoT applications. Combining edge computing, parallel processing and an AI deep learning processor, the new solution provides energy efficiency for stand-alone AI inference nodes designed for smart manufacturing and other industrial applications.

Foxconn has combined its high-density, fan-less edge computing solution BOXiedge with Socionext’s high-efficiency parallel processor SynQuacer SC2A11, and the Hailo-8 deep learning processor.

Taipei-based Foxconn is a smart manufacturing specialist focused on the electronics and embedded technologies markets. Yokohama-based Socionext is a developer of SoC solutions for video and imaging systems. Tel Aviv-based Hailo is a chip maker of AI and deep learning processors.

Foxconn has already deployed several in-house developed AI solutions on different production lines, leading to an improvement in reporting accuracy from 95% to 99% and a reduction of at least one third of the operating costs for appearance defect inspection projects.

“Our vision at Foxconn is to pave the way for next generation AI solutions,” said Gene Liu, VP of Semiconductor Subgroup at Foxconn Technology Group. “We are confident that this strategic collaboration with our long-standing partner, Socionext, alongside Hailo, will do more than that. We recognise the great potential in adopting AI solutions for a multitude of applications, such as tumour detection and robotic navigation. This is why we are proud to say that our edge computing solution combined with Hailo’s deep learning processor will create even better energy efficiency for stand-alone AI inference nodes to positively impact rapidly evolving sectors including smart cities, smart medical, smart retail, and industrial IoT.”