Smart and Sustainable Ice Cream Making Through Edge Machine Learning

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Authors: Filippo Tabanelli, Simon Dahdal, Nicolas Belletti, Elena Bellodi, Franck Ngatcha, R. Lazzarini, Cesare Stefanelli, Mauro Tortonesi
Cited by: 1
References: 40

Abstract

The manufacturing process of frozen dairy desserts, such as ice cream and gelato, is very sensitive to human errors in ingredient preparation: even minor variations in the ingredient mix can lead to quality issues and material waste. To become more sustainable, next generation ice cream making machines need to implement intelligent and adaptive processes that are both efficient and forgiving of human mistakes in mixture preparations. Toward that goal, we developed Hard-O-Tronic AI-driven (HOT-AI), a novel edge AI solution specifically designed for Carpigiani’s ice cream making machines. Leveraging the innovative multimilestone classification methodology, HOT-AI performs inference at multiple stages—or milestones—during the ice cream making process, with increasing accuracy over time. This enables HOT-AI to take corrective actions by adapting the preparation process accordingly, thus improving batch-to-batch uniformity, minimizing ingredient waste, and enhancing production efficiency, cost-effectiveness, and sustainability. HOT-AI has been successfully validated under real production conditions, and its large-scale implementation is planned across Carpigiani Group machines.

Fields of Study & Subjects

Food Supply Chain Traceability Food Drying and Modeling Machine Learning in Materials Science

Publication details

Journal / source
IEEE Transactions on Industrial Informatics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
22
Issue
4
Pages
2909–2918
Publication date
22 January 2026
Language
EN