I. Core Achievement Announcement

The R&D Center of Henan Zoomlion DeMei Machinery Manufacturing Co., Ltd. (hereinafter referred to as “Zoomlion DeMei”) announced that its independently developed “Huiyan” AI Vision Intelligent Sorting System has passed pilot testing and will soon be applied to a new generation of waste sorting production lines. Based on multispectral recognition and deep learning algorithms, the system realizes precise sorting of construction waste with complex compositions.

II. R&D Background and Technological Breakthroughs

Industry Demand Driver

With the advancement of the “Zero-Waste City” initiative, traditional sorting methods can no longer meet the production requirements for high-purity recycled aggregates, creating an urgent need for technological upgrading.

Key Technological Innovations

After two years of technical research and development, the R&D team of Zoomlion DeMei successfully integrated AI visual recognition technology into the solid waste sorting process. The system can accurately distinguish between concrete, bricks and tiles, wood, plastic, and non-ferrous metals, effectively solving the problem of residual lightweight impurities that are difficult to handle with traditional air separation and magnetic separation methods.

III. Pilot Test Results

According to a technical engineer from Zoomlion DeMei, during the testing phase, the system achieved an identification accuracy rate exceeding 98% for contaminants such as plastic and wood chips mixed in construction waste. This achievement means that customers can produce cleaner recycled aggregates, which can be directly used in the production of high-standard recycled building materials, significantly enhancing product value.

IV. Significance of Technological Application

• Marks a crucial step for Zoomlion DeMei in transitioning from traditional mechanical manufacturing to “smart manufacturing”;
• Provides more reliable technical support for downstream resource recovery enterprises and contributes to the upgrading of construction waste resource utilization.