Presenter: OMiLAB NPO and ULBS

Presenter: ULBS

1. Innovative Monitoring System for Beer Fermentation
The research project is part of an innovative vision to develop an advanced system for monitoring and analyzing the beer wort fermentation process using digital image processing technologies and artificial intelligence, implemented in MATLAB 2024. The project is designed to meet the four specific criteria resilience, digitalization, sustainability (green), and human-centered focus, to optimize the fermentation process. The automatic monitoring system uses anomaly detection and constant analysis of fermentation variables to ensure a stable and robust process. By identifying potential issues early on, rapid corrective actions can be implemented to prevent product quality degradation.

2. Applying AI Tools for Modeling, Predicting and Managing the White Wine Fermentation Process
This webinar section reveals two of the challenges faced by Romania and proposes a sustainable and simple solution for its wine industry. First, substantial areas with vineyards that may produce qualitative wine, and second, the very low digitalization rate of industrial sectors. More precisely, this work proposes a solution for digitalizing the fermentation process of white wine, allowing it to be adapted for other control techniques (i.e., knowledge-based systems, intelligent control). Our method consists of implementing a pre-trained multi-layer perceptron neural network, using genetic algorithms capable of predicting the concentration of alcohol and the amount of substrate at a certain point in time that starts from the initial configuration of the fermentation process. The purpose of predicting these process features is to obtain information about status variables so that the process can be automatically driven. The main advantage of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors.
The software application allows configuring a Neural Network and/or a Genetic Algorithm that can simulate the white wine fermentation and based on your datasets you can observe the “Alcohol Concentration” and “Substrate” evolution in the fermentation process and after training you can test with some different parameters to see the results that can be obtained.

Presenter: ULBS

The use case analyses the particularities of implementing an aerial monitorization system of agricultural crops with the help of drones, while concentrating on evaluating the quality of the agricultural work, as well as of the damage caused by excessive pasture. In addition, the ways in which the drones lead to a higher level of knowledge of the plants’ development in different areas of the terrain is also explored. The drones are connected to intelligent platforms and are equipped with new technologies to achieve useful utensils (3D maps). They are also able to receive information about the plants’ development, the normalized index of plants, etc.