On May 17, the 2024 (Second) Machine Vision Technology and Application Summit successfully concluded, where APQ's AK series products won the "2024 Machine Vision Industry Chain TOP30" award.

The 2024 (Second) Machine Vision Technology and Application Summit, organized by Gaogong Robotics and the Gaogong Robotics Industry Research Institute (GGII), grandly opened in Shenzhen on May 17.

During the summit, APQ's Deputy General Manager, Javis Xu, delivered a speech titled "Application of AI Edge Computing in Industrial Machine Vision," where he deeply analyzed the diverse needs of industrial cameras and the limitations of traditional IPC solutions. He explained how APQ cleverly addresses these challenges, bringing a new perspective to the industry.

Mr. Xu focused on introducing APQ's new generation product—the E-Smart IPC flagship magazine-style intelligent controller AK series. This series adopts an innovative 1+1+1 model, meaning the main unit is paired with a primary magazine, auxiliary magazine, and soft magazine, providing a highly modular and adaptable intelligent control solution for the machine vision field.

At the summit, the APQ AK series was recognized for its outstanding performance and innovative capabilities in the machine vision field, earning it a spot on the "2024 Machine Vision Industry Chain TOP30" list.

The APQ booth became a focal point at the summit, with the AK series and E7DS products attracting a large number of professionals who engaged in numerous inquiries and lively discussions. The atmosphere at the booth was very enthusiastic, with a steady stream of customer consultations.

Through this summit, APQ once again proved its profound expertise and strong capabilities in AI edge computing and industrial machine vision, as well as the market competitiveness of its new generation AK series products. In the future, APQ will continue to delve into AI edge computing technology research, continuously launching innovative products and services to contribute more wisdom and strength to the advancement of industrial machine vision applications.