Skin Condition Based Smart Cosmetics Suggestion System Using Artificial Intelligence

Authors

  • P. Laxmi Department of Computer Science and Engineering, Vijay Rural Engineering College, Rochis Valley, Manikbhandar, Telangana, India Author
  • Adani Nandini Department of Computer Science and Engineering, Vijay Rural Engineering College, Rochis Valley, Manikbhandar, Telangana, India Author
  • Bakka Akhila Department of Computer Science and Engineering, Vijay Rural Engineering College, Rochis Valley, Manikbhandar, Telangana, India Author
  • Gandhari Harshith Reddy Department of Computer Science and Engineering, Vijay Rural Engineering College, Rochis Valley, Manikbhandar, Telangana, India Author

Abstract

Globally, the demand for cosmetics has increased recently, especially in the skin care sector. With so many choices available online, many consumers find it difficult to choose a product that complements their skin tone. Every person has unique skin, so it can be difficult to choose cosmetics that work well for them. It is important to identify cosmetics that do not cause allergies or other adverse reactions in clients. The perfect solution to this problem is to use AI (Artificial Intelligence) algorithms. This paper presents Skin Condition Based Smart Cosmetics Suggestion System using Artificial Intelligence. The described model of Skin Condition-Based Smart Cosmetics Suggestion System uses a Convolutional Neural Network (CNN) classification technique. This recommendation system helps users identify their skin type and suggests cosmetics. The AI-based Cosmetics Suggestion System outperforms the traditional Cosmetics Suggestion System in terms of Accuracy and Precision.

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Published

13-03-2026

Conference Proceedings Volume

Section

Articles

How to Cite

Laxmi, P. ., Nandini, A. ., Akhila, B. ., & Reddy, G. H. . (2026). Skin Condition Based Smart Cosmetics Suggestion System Using Artificial Intelligence. DMPedia Lecture Notes in Computer Science & Engineering, IMPACT26, 432-441. https://digitalmanuscriptpedia.com/conferences/index.php/DMP-LNCSE/article/view/124