Aroma AI

Discover the perfect fragrance for you with our AI powered fragrance finder. Simply answer a few questions and let our algorithm match you with the perfect scent.

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Inspiration

Finding the perfect fragrance can be overwhelming, with countless options and complex scent profiles. We wanted to simplify this process using machine learning, helping users discover their ideal scent effortlessly.

What it does

Aroma AI is an intelligent fragrance finder that matches users with the perfect scent based on their preferences. By analyzing fragrance notes, accords, and packaging aesthetics, our algorithm provides personalized recommendations tailored to individual tastes.

How we built it

We built Aroma AI using a combination of:

  • Frontend: HTML, CSS, and JavaScript for an intuitive user interface.
  • Backend: Node.js with a database to store fragrance profiles and user inputs.
  • Machine Learning: A recommendation algorithm trained on fragrance data, analyzing scent compositions and user preferences.
  • Python & OpenCV: Python is used for data processing and machine learning, while OpenCV helps analyze visual elements of perfume packaging to enhance recommendations based on design aesthetics.

Challenges we ran into

  • Structuring fragrance data to ensure accurate recommendations.
  • Fine-tuning the ML model for a balance between accuracy and variety.
  • Using OpenCV to extract meaningful insights from perfume packaging.

Accomplishments that we're proud of

  • Successfully integrating machine learning for personalized fragrance recommendations.
  • Creating a seamless and user-friendly interface.
  • Implementing image analysis to enhance fragrance suggestions.

What we learned

  • The complexity of fragrance classification and how different factors influence scent preferences.
  • How to optimize machine learning models for personalized recommendations.
  • The role of aesthetics in user decision-making and how OpenCV can enhance product selection.

What's next for Aroma AI

  • Expanding our database with niche and luxury fragrances.
  • Refining our AI model with user feedback for even better recommendations.
  • Developing a mobile app for an interactive, on-the-go experience.
  • Exploring partnerships with fragrance brands for direct product integration.
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