Technologies - Cutting-Edge Technologies for Recycling

The cleaner recyclables are sorted during the resource recovery process, the higher their reuse value. RECO Vista leverages state-of-the-art deep learning technology to integrate cutting-edge applications into existing production lines, ensuring precise quality inspection of target materials. This guarantees high-purity sorting, maximizing recyclability and boosting factory profitability.

By continuously collecting and training on real-world production line data, RECO Vista updates its dataset to adapt to diverse compositions of recyclables. Equipped with low-power hardware, it seamlessly integrates into existing production lines with minimal effort. Through precise inspection data, RECO Vista enhances resource recovery efficiency, adding value to the circular economy.

The high-speed sorting robotic arm ensures stable sorting speed and precision, effectively classifying various types of recyclables to improve recovery efficiency and collect more valuable materials. Additionally, it can be customized to fit the layout of existing recycling facilities, ensuring a smooth transition and minimizing the time costs associated with factory upgrades.

RECO Delta seamlessly integrates with RECO Cognita and RECO Vista, providing real-time data monitoring and report generation through an intuitive visual interface to enhance management efficiency. The system also supports on-demand reconfiguration of storage bin categories, making the recycling process more flexible and efficient.

Built on data science, RECO Cognita delivers intelligent management solutions, leveraging visualized data to support decision-making, enabling factories to accurately forecast profitability and enhance their competitive edge.

Through data collection and analysis, we develop customized management systems that ensure clear presentation of critical information. Our high-performance web application supports cross-platform access and integrates IoT and edge computing devices for real-time factory monitoring, maximizing equipment performance, improving production efficiency, and optimizing operational outcomes.