Intelligent Educational Platform for Nail Art Training

Kseniia Pereshliuga

Citation: Kseniia Pereshliuga, "Intelligent Educational Platform for Nail Art Training", Universal Library of Innovative Research and Studies, Volume 02, Issue 02.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This study explores the potential of using simulators in nail art training, integrating artificial intelligence (AI), 3D printing, and the Internet of Things (IoT). The research addresses the challenges of skill variability and safety in traditional nail art education by proposing a methodology that ensures high-precision replication of decorative techniques, modeling of complex cases, and automated feedback with personalized recommendations. The conducted study demonstrates improved accuracy in technique execution, reduced skill acquisition time, and increased learner satisfaction. The findings confirm the hypothesis that integrating digital technologies into nail art training contributes to standardization and enhances the quality of professional preparation, opening opportunities for further commercialization and implementation in beauty industry educational programs. The insights presented in this study are of interest to researchers and professionals in educational technologies, computer modeling, and artificial intelligence, focusing on the development of integrated simulation platforms to improve professional training quality in the beauty industry. The integration of practical techniques, complex scenario modeling with AI-driven feedback, and dynamic progress monitoring with adaptive skill assessment creates new prospects for both theoretical research in interdisciplinary fields and the practical implementation of innovative educational solutions in professional nail art training.


Keywords: Artificial Intelligence, 3D Printing, Internet of Things, Simulator, Nail Art, Training, Feedback, Modeling, Personalized Recommendations.

Download doi https://doi.org/10.70315/uloap.ulirs.2025.0202004