Skinie Buddy: An AI-Powered Skincare Detection, Guidance and Routine Companion System
Skinie Buddy: An AI-Powered Skincare Detection, Guidance and Routine Companion System
- Sai Prasad¹, S. Rahul², A. Swathi³, K.Larishma⁴, D.Chandu⁵
¹Senior Assistant Professor, Computer Science and Engineering, Sanketika Vidya Parishad Engineering College, Visakhapatnam, India
²³⁴⁵B.Tech Final Semester, Computer Science and Engineering, Sanketika Vidya Parishad Engineering College, Visakhapatnam, India
Abstract - Skinie Buddy is an AI-enabled web-based platform developed to deliver personalized skincare recommendations through automated skin analysis and interactive assistance, addressing skincare misuse and misinformation arising from limited access to affordable dermatological services. The system utilizes a CNN, based on the EfficientNet-B0 architecture with transfer learning to classify skin types including oily, dry, normal, acne-prone, and combination skin, using a dataset representing diverse skin tones. Built on a scalable web architecture, the platform integrates image-based skin assessment with a conversational AI module to provide real-time, context-aware guidance, ingredient compatibility analysis, and personalized routine management features such as usage tracking and streak monitoring. Skinie Buddy aims to encourage informed skincare practices and enhance overall skin health through an accessible, evidence-based digital solution.
Key Words: EfficientNet-B0, skin tone diversity, XGBoost, LightGBM, conversational AI, Skincare Recommendation, Streak monitoring, Full-Stack Web Application