Active Lab: AI for food waste monitoring systems

SESSION AL06 + AL07 / 15 October 2025 / 09:00 - 12:30
Active Lab: AI for food waste monitoring systems

Organised by:
Mengting Yu, University of Tuscia (IT)
Luca Secondi, University of Tuscia (IT)

This active lab is designed as an extension to the oral presentation "AI and Food Sharing: Revolutionizing Food Waste Tracking and Mitigation" (scheduled in Session E05), which leverages AI and computer vision technologies to automate the precise quantification and identification of food waste in real-life cases. We aim to provide maximum engagement with participants and offer a hands-on opportunity for those interested in AI technology applications, food waste, and data science. The lab will demonstrate the application of AIpowered food waste identification and quantification. Moreover, each participant can expect to gain practical knowledge about how to build a simple food waste tracking and monitoring system. We will provide a few hardware sets for testing, open-source AI models, and programming codes.
Through this active lab, we expect participants to become more familiar with AI and computer vision technologies that can be used to identify and quantify food waste at the consumer level.
The activities that will be carried out in this active lab are:

• Pre-lab: All confirmed participants will be requested to contribute to the data collection of this lab. We will communicate with each participant to submit some food (leftover) images and the respective measured weight by email. Those images will be merged with the existing database and will be used for AI applications and data analysis during the lab.
• Presentation: A short presentation will cover the topics of consumer food waste, food waste quantification and composition, and digital innovations for food waste monitoring (e.g. AI technologies).
• Training: We will deliver a full training on how to build a food waste tracking and monitoring system with AI and computer vision technologies. Participants will work in small groups and be provided with a set of hardware, and they will learn how to use Python to program the automatic monitoring system.
• Analysis: All participants will use Excel, Python, or R Studio to carry out statistical analysis on the data elaborated during the workshop, evaluating the accuracy of the automatic monitoring system. Furthermore, there will be an open discussion on the potential to train or fine-tune an AI system on collected data to improve the weight estimation accuracy.