There are increasing international concerns in reducing plastic waste. Although cosmetic companies proclaim environment-friendly marketing strategies, it seems to be still hard to replace the plastic cosmetic containers with dissolvable materials. Also if the purchased cosmetics do not fit for customer’s demands, they are likely to be thrown away. Eventually it causes significantly shorter life cycle of cosmetics and plastic wastes. This study intends to prolong the life cycle of cosmetics by exactly informing consumers what their skin conditions are, thereby what cosmetics they should select. Therefore, this study introduces an application that accurately diagnose the skin condition by the Big Data analysis, and also helps customers select the right cosmetics. First of all, a device with diagnosing functions periodically measure customers’ skin conditions, and then the measured data are analyzed to search for appropriate chemicals and ingredients. Based on the analytics, customers are eventually educated concerning the cosmetics appropriate for my skin type among numerous types of cosmetics. The more the customer accumulate the historical skin data and their purchase, the more refined choices of cosmetics would be recommended. Additionally, when customers purchase cosmetics, the application indicates whether or not the cosmetics of interest fit for customer’s skin condition intuitively and quickly using the AR (Augmented Reality) based ingredient analytics. In short, this paper purpose to promote the educated choice of cosmetics with which customers are satisfied for a long term, and reduce the plastic wastes due to the wrong choice of the cosmetics.
Gayoung Kang, Seoul National University of Science and Technology, South Korea
Sean Hay Kim, Seoul National University of Science and Technology, South Korea
This paper is part of the IICSEEHawaii2019 Conference Proceedings (View)
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