Goal:

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.

Necessity and challenges:

Varga-Szárnyas Kft. recognizes the importance of maintaining high food safety and quality standards to sustain growth. As the company expands, it faces challenges in maintaining quality assurance amidst increasing production volumes. By implementing AI-supported quality control measures, the company aims to overcome these challenges and ensure consistent quality without relying solely on manual intervention.

Expected benefits:

• A 15% improvement in production efficiency, allowing for increased output without compromising quality.
• Overall improvement in product quality by 10% through AI-supported visual quality control.
• Affordable AI solutions for agrifood SMEs in the future through the development of a cloud-based agri-food database and transfer learning capabilities of deep neural networks.

Partners:

• Varga Szárnyas Kft. - https://vargaszarnyas.hu/
• Mortoff Kft. - https://mortoff.hu/en/