Implementation projects

The REACH Agrifood AI-supported Visual Quality Control (R-AI-VQC) project aims to enhance quality control in food packaging through real-time monitoring and artificial intelligence (AI) analysis. By collecting real-time production data on the packaging process and implementing AI-supported video analysis, the project seeks to improve quality assurance and safety measures. Additionally, the project aims to develop a cloud solution to streamline model training in the agrifood industry, further enhancing efficiency and accuracy.

The PREVAI project uses artificial intelligence to improve demand forecasting and raw material purchasing in cream cheese manufacturing. By integrating AI models across the supply chain, the project aims to minimize waste, reduce stock shortages, and optimize end-to-end production efficiency—from forecasting demand to purchasing and processing raw materials.

The project aims to develop technology utilizing hardware and software components to address various issues in mineral water production lines. These include detecting bottles with missing printed due dates, insufficient water fill levels, misaligned bottle caps, coloration changes in bottle labels, and pre-forms. By implementing this technology, the project seeks to enhance quality control, minimize production waste, and improve sustainability within the bottled beverage industry.