| Issue |
EPJ Web Conf.
Volume 377, 2026
15th International Physics Seminar (IPS 2026)
|
|
|---|---|---|
| Article Number | 06009 | |
| Number of page(s) | 9 | |
| Section | Applied Technology in Physics | |
| DOI | https://doi.org/10.1051/epjconf/202637706009 | |
| Published online | 02 July 2026 | |
https://doi.org/10.1051/epjconf/202637706009
Instrumentation and Control System for AI-Based Skin Type Classification and Automated Skincare Sample Dispensing Using Computer Vision and Robotic Vending
1 Faculty of Economics and Business, Universitas Negeri Jakarta, 13220, Jakarta, Indonesia
2 Faculty of Information Technology, Batam Institute of Technology, 29425, Batam, Indonesia
3 Faculty of Economics, Muhammadiyah University of Sukabumi, 43113 Sukabumi, Indonesia
4 Faculty of Business, Accountancy and Law, SEGi University, 47810 Kota Damansara, Malaysia
5 Faculty of Business and Communications, INTI International University, 71800, Nilai, Malaysia
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 2 July 2026
Abstract
The novelty of this study lies in integrating computer vision, CNN-based skin classification, AI recommendations, voice interaction, and robotic vending into a single retail platform for body skincare services. Unlike conventional retail systems, the proposed platform combines skin analysis, personalised recommendations, interactive communication, and automated product dispensing within one system. This study aims to develop and evaluate an AI-based skincare recommendation system that identifies customer skin types through image analysis and automatically dispenses product samples based on the recommendation results. Using a Design Science Research approach, a smart robotic vending prototype was developed by integrating image acquisition, AI processing, and robotic dispensing components. The prototype successfully demonstrated skin classification, recommendation generation, voice interaction, and automated sample dispensing. Functional testing confirmed the feasibility of real-time image acquisition, AI-based classification, recommendation delivery, and product dispensing. The results demonstrate the feasibility of supporting intelligent customer interaction through automated skin analysis, personalised skincare recommendations, and integrated sample dispensing.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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