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Voice-Enabled Skin AI Analyzer

Introducing a groundbreaking project that combines cutting-edge AI technology with user-friendly voice assistance to revolutionize skincare analysis.

視頻

技術堆疊

Python

描述

Project Description:

Revolutionizing Skincare is an innovative web-based solution that blends advanced artificial intelligence with intuitive voice assistant technology to transform the way users approach skincare. Designed for convenience and precision, this project allows users to analyze their skin condition hands-free through voice commands, making the experience accessible, interactive, and user-friendly.

Key Features:

  • AI-Powered Skin Analysis: Accurately detects skin type, assesses sebum levels, pores, wrinkles, and provides age estimations using image processing techniques such as HSV analysis, Canny edge detection, and Laplacian variance.

  • Voice Assistant Integration: Enables users to navigate the platform, capture facial images, and receive real-time feedback and guidance through voice commands.

  • Personalized Reports: Generates detailed, easy-to-understand reports with skincare suggestions tailored to each user’s unique skin profile, addressing concerns like acne, wrinkles, and dark spots.

  • Visualizations: Presents skin metrics through graphical representations to simplify interpretation and improve engagement.

Why It Stands Out: Unlike traditional skin analysis tools, this solution integrates a voice assistant for complete hands-free interaction, offering a holistic, personalized skincare assessment experience.

Future Roadmap: Plans include enhancing AI accuracy through machine learning, integrating wearable skin sensors for real-time data, and enabling telemedicine features for virtual dermatologist consultations.

Team Members: Aarav Jai, Arein Jain, Aryan Tripathi, Ayush Singhal, Shivansh Saxena

黑客松進展

During the hackathon, our team made significant strides in transforming our idea into a functional prototype: Ideation & Planning: Finalized the concept of integrating voice commands with AI-driven skin analysis. Allocated tasks among team members based on expertise. Frontend Development: Built a responsive web interface allowing users to interact with the system. Integrated webcam access for capturing facial images. Voice Assistant Integration: Enabled voice-controlled image capture and navigation. Added real-time spoken feedback to guide users through the process. AI-Based Image Analysis: Implemented core skin analysis algorithms: Skin type detection using HSV color space. Wrinkle detection via Canny edge detection. Sebum and pore analysis using brightness and Laplacian variance. Report Generation: Developed a system to compile results into a visually rich report. Included tailored skincare recommendations based on detected conditions. Testing & Refinement: Conducted multiple tests to improve accuracy and voice interaction reliability. Ensured a smooth user experience with minimal latency. By the end of the hackathon, we successfully created a working demo that showcases the full flow—from voice-activated image capture to personalized skin reports.

籌資狀態

Nil
團隊負責人
AArein Jain
專案連結
行業
AI