{"id":5760,"date":"2025-09-17T12:26:11","date_gmt":"2025-09-17T10:26:11","guid":{"rendered":"https:\/\/www.axians-ias.com\/?p=5760"},"modified":"2025-09-30T13:47:03","modified_gmt":"2025-09-30T11:47:03","slug":"webcast-material-detection-analysis-with-optocycle-and-vas-yard-management","status":"publish","type":"post","link":"https:\/\/www.axians-ias.com\/en\/webcast-material-detection-analysis-with-optocycle-and-vas-yard-management\/","title":{"rendered":"WebCast: Material recognition \/analysis with Optocycle and VAS Yard Management"},"content":{"rendered":"
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OCTOBER 14, 2025: 2:00 p.m. \u2013 2:30 p.m.<\/div>

Material recognition \/ analysis with Optocycle and VAS Yard Management<\/h2>

Safe and fast processes for waste delivery and building material delivery<\/h3><\/div>[vc_column_text]Secure and efficient delivery and collection processes are a major challenge for many companies in the bulk goods industry and the circular economy. An important aspect of this is ensuring that the material corresponds to the predefined specifications in the delivery and that it can be clearly assigned to a waste code or even to an exact material type. This requires reliable and automated material recognition\/analysis, the results of which can be used directly in the delivery workflow.\r\n\r\nIn our webcast, we show you how these requirements can be met with Optocycle<\/a>‘s AI-supported camera and software solution in combination with Axians VAS Yard Management<\/a>. For both delivery and dispatch processes, the material on the truck’s loading area is scanned with Optocycle and analyzed with AI-based evaluation software with regard to a variety of material attributes. These results can then be used in VAS Yard Management to compare with predefined waste codes or material types and, based on this, it can be determined \u2013 in a configurable manner \u2013 whether everything is correct or whether manual intervention is required. This leads to consistent, verifiable decision-making processes at all times, minimizes errors, and reduces manual checking processes. Administrative expenses and follow-up costs, e.g., due to incorrect loading, can thus be significantly reduced.\r\n\r\n \r\n\r\nIn the webcast, we address the following questions:<\/strong>\r\n