To avoid food waste and for quality assurance, continuous digital quality recording and mapping of the entire supply chain is of central importance. More food safety and less waste are achieved, for example, by forecasting the state of freshness. Sensors and optical technologies use AI methods to assign a freshness level accordingly and prediction methods determine the freshness of the food along the supply chain using machine learning techniques. In this session, you'll learn how AI-controlled processes for quality classification can be implemented technically and economically in companies.

Available on anugafoodtec @home

15:30-15:40 Opening and Chair

Prof. Dr.-Ing. Bernd Lindemann, Hochschule Geisenheim University, Geisenheim, Germany

15:40-16:05 smart.CONSERVE: intelligent Containers within the food industry

Malek Wolf, Packwise GmbH, Dresden, Germany  

16:05-16:30 Movi-Q: Use of artificial intelligence to detect product defects in the food industry

Thorsten Lameyer, DIL Deutsches Institut für Lebensmitteltechnik e. V., Quackenbrück, Germany

16:30-16:55 Quality monitoring along the food process chain using biosensors and artificial intelligence

Ramtin Rahmanzadeh, Universität Lübeck, Germany

16:55-17:00 Summary and closing

Prof. Dr.-Ing. Bernd Lindemann, Hochschule Geisenheim University, Geisenheim, Germany