Mirror Match

For a product design project for my Pervasive Interaction Design class, I collaborated with a team to develop Mirror Match, a tool designed to revolutionize the morning routine. Leveraging augmented reality technology, Mirror Match provides personalized styling suggestions and streamlines outfit selection by:

  • Helping confidently select outfits through a personalized recommendation system.

  • Reducing the time spent trying on multiple outfits through the AR virtual try-on feature.

  • Organizing clothes through an integrated smart hanger system simplifies the search for specific garments.

A visualization of our final system concept, with a smart mirror and integrated clothes hangers

Product Designer

Conversational Designer

UX Researcher

UX Designer

Arduino Developer

Roles

Timeline

January - April 2024

Ideation

Contextual Inquiry

Diary Study

Survey

Empathy Map

Journey Map

User Enactments

Storyboards

Prototyping

Conversational Design

Skills

Figma

Arduino

Google Forms

Qualtrics

Tools

Introduction: Problem Space and Discovery

Young professionals want to express their personal style, but choosing an outfit in the morning can be stressful and time-consuming. Many struggle with indecision, rushing through their routine, or feeling dissatisfied with their final choice.

Our team initially brainstormed 80+ ideas for connected IoT devices which focused on morning and evening routines. After conducting user research, we narrowed down our topic to a smart mirror to support young professionals and their morning and evening routines.

Research process

Our low-fidelity prototypes used in our team’s user enactments

🔍 Contextual Inquiry → To explore how young professionals behave in their home environments, we conducted 7 contextual inquiries with individuals living alone or with one roommate, shadowing them through their morning and evening routines at home.

📖 Diary Study → We conducted a 5-day diary study with 8 participants who documented their morning and evening routines, highlighting significant deviations and emotional responses.

📋 Survey → We distributed a survey to 68 respondents to understand their daily routines, pinpoint frustrating tasks, and identify favorite activities.

🎭 User Enactments → We tested 4 interactive, very low-fidelity prototypes in 12 total scenarios using a Speed Dating Matrix to assess user preferences, refine our ideas, and adjust the level of automation that users desired.

Key Insights

Indecision in outfit selection causes stress in the morning

Users struggled with picking an outfit quickly, often feeling rushed or second-guessing their choices.

Morning routines are time-constrained, and users want efficiency

Many participants felt pressed for time, especially when getting ready for work, leading to frustration

Weather and special events play a key role in outfit choices

Users often checked the weather and thought about events on their schedule for that day when selecting an outfit.

Users value autonomy but appreciate guided recommendations

While participants didn’t want a fully automated system, they liked curated outfit suggestions they could adjust.

Final System Concept and Key Features

AR Mirror Technology: See Before You Wear

Mirror Match’s built-in augmented reality display allows users to preview outfits on themselves in real time. Instead of trying on multiple outfits, users can visualize their choices instantly, helping them make faster and more confident decisions.

💡 Impact:

  • Saves time by eliminating the need to try clothes on physically.

  • Increases confidence in outfit choices.

  • Encourages creative styling by showing new combinations.

Smart Hangers: Find What You Need Instantly

The smart closet system integrates with Mirror Match to highlight the exact clothing item the user selects. Smart hangers light up using LED technology, allowing users to locate items quickly.

💡 Impact:

  • Reduces morning frustration of searching for clothes.

  • Keeps the closet organized and easy to navigate.

  • Supports busy professionals in streamlining their routine.

Personalized Outfit Recommendations

Mirror Match suggests outfits tailored to the day’s weather, events, and personal style. The system learns from past choices to refine its recommendations over time.

💡 Impact:

  • Reduces decision fatigue with curated suggestions.

  • Ensures outfits are appropriate for the day’s plans.

  • Enhances personal style confidence with AI-driven insights.

Motion-Activated, Hands-Free Experience

The mirror automatically turns on when a user approaches, making the experience seamless and effortless.

💡 Impact:

  • Provides an intuitive, touch-free interaction.

  • Enhances convenience, especially during busy mornings.

  • Makes smart technology feel friendly and helpful.

Reflection

This project was really fun to do because it was so different than the digital design that I am used to doing. Using the physical space with the mirror and attached sensors added totally different consideration to our design. It was really interesting to apply the same UX research and design skills to an IoT prototype, since it pushed me to think more creatively.

For example, we realized that a product such as Mirror Match has tons of use cases that need to be accounted for. In our prototype, we identified around five distinct “getting dressed” scenarios and we could have included more. Before launching the product, we would have to do further research to make sure that the product is designed to be prepared for many other scenarios, such as various special occasions, vacation outfit planning, or last minute costumes, just to name a few.