Development of an Emotion Recognition System to Monitor Childrens Emotions in Preschool Institutions
Nazgul D. Lena Z. Banu Y.
2025Institute of Electrical and Electronics Engineers Inc.
International Conference on Computer Science and Engineering, UBMK
2025Issue 2025824 - 829 pp.
This article presents an innovative artificial intelligence-based system developed for the real-time monitoring of childrens emotional states within preschool settings. The system employs a deep convolutional neural network (CNN) specifically designed to recognize emotions through the analysis of facial expressions. The FER-2013 dataset served as the foundational data source for training a model that categorizes emotions into seven distinct groups. Throughout the training and validation phases, the model achieved an accuracy rate of 81.32%. Results generated by the system are disseminated to educators and parents via a web application built on the Django framework, as well as through a Telegram bot interface. The proposed methodology enhances the continuous observation of childrens psycho-emotional states in kindergartens, promotes timely intervention strategies, and fosters improved communication between parents and educational institutions.
artificial intelligence , convolutional neural network , emotion recognition , FER-2013 , preschool children , real-time monitoring
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L.N. Gumilyov Eurasian National University, Department of Artificial Intelligence Technologies, Astana, Kazakhstan
L.N. Gumilyov Eurasian National University
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026