BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:Europe/London X-WR-TIMEZONE:Europe/London BEGIN:VEVENT UID:10-14@ulbsibiu.community.omilab.org DTSTART;TZID=Europe/Vienna:20250320T130000 DTEND;TZID=Europe/Vienna:20250320T134500 DTSTAMP:20250418T083114Z URL:https://ulbsibiu.community.omilab.org/events/codemo-webinar-modernizin g-agricultural-practices-and-food-engineering-processes-using-ai-robotics- and-iot/ SUMMARY:CoDEMO Webinar: Modernizing Agricultural Practices and Food Enginee ring Processes using AI\, Robotics and IoT DESCRIPTION:The focus of this webinar is on two main topics:\n1. Applying A I Tools for Modeling\, Predicting\, Monitoring and Managing the Alcoholic Fermentation Process\nInnovative Monitoring System for Beer Fermentation\n The research project is part of an innovative vision to develop an advance d system for monitoring and analyzing the beer wort fermentation process u sing digital image processing technologies and artificial intelligence\, i mplemented in MATLAB 2024. The project is designed to meet the four specif ic criteria resilience\, digitalization\, sustainability (green)\, and hum an-centered focus\, to optimize the fermentation process. The automatic mo nitoring system uses anomaly detection and constant analysis of fermentati on variables to ensure a stable and robust process. Rapid corrective actio ns can be implemented to prevent product quality degradation by identifyin g potential issues early on.\nApplying AI Tools for Modeling\, Predicting and Managing the White Wine Fermentation Process\nThis webinar section rev eals two of the challenges faced by Romania and proposes a sustainable and simple solution for its wine industry. First\, substantial areas with vin eyards that may produce qualitative wine\, and second\, the very low digit alization rate of industrial sectors. More precisely\, this work proposes a solution for digitalizing the fermentation process of white wine\, allow ing 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 c apable of predicting the concentration of alcohol and the amount of substr ate at a certain point in time that starts from the initial configuration of the fermentation process. The purpose of predicting these process featu res is to obtain information about status variables so that the process ca n be automatically driven. The main advantage of our application is to hel p experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors.\nThe software applic ation allows configuring a Neural Network and/or a Genetic Algorithm that can simulate the white wine fermentation and based on your datasets you ca n observe the “Alcohol Concentration” and “Substrate” evolution in the fermentation process and after training you can test with some differ ent parameters to see the results that can be obtained.\n2. Aerial crop mo nitorization system of agricultural crops\nThe use case analyses the parti cularities of implementing an aerial monitorization system of agricultural crops with the help of drones\, while concentrating on evaluating the qua lity of the agricultural work\, as well as of the damage caused by excessi ve pasture. In addition\, the ways in which the drones lead to a higher le vel of knowledge of the plants’ development in different areas of the te rrain 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’ developme nt\, the normalized index of plants\, etc.\n\n \;\nWebinar Recording: https://www.youtube.com/watch?v=mIQSrx_FGTQ ATTACH;FMTTYPE=image/jpeg:https://ulbsibiu.community.omilab.org/wp-content /uploads/sites/10/2025/04/banner.jpg LOCATION:https://us06web.zoom.us/j/87884936585 END:VEVENT BEGIN:VTIMEZONE TZID:Europe/Vienna X-LIC-LOCATION:Europe/Vienna BEGIN:STANDARD DTSTART:20241027T020000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET END:STANDARD END:VTIMEZONE END:VCALENDAR