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FridgeBrain

An AI app for your refrigerator.

Background

BACKGROUND

01

Research

Visually impaired individuals are more prone to malnutrition due to accessibility challenges as indicated by previous research.

02

​​Visually impaired people have reported difficulty shopping for, eating, and preparing meals.

03

Food packaging often relies on visual information, creating challenges for visually impaired individuals. AI system that can read aloud product details and detect freshness of grocery can significantly improve their life.

BACKGROUND

Problem Statement

Visually impaired people have difficulty checking food expiration dates and monitoring food freshness.

Difficulty finding food with nutritional value.

Difficulty figuring out recipes.

Solution

SOLUTION

Prototype

SOLUTION

Demo Video

Method

METHOD

Survey Design

Study Type

Single Factor Design

Participants

32

Independent Variable

Use of FridgeBrain App

Dependent Variables
  • Perceived helpfulness of food storage listing.
  • Perceived helpfulness of expiration alerts.
  • Perceived helpfulness of nutritional suggestions.
  • Perceived helpfulness of recipe suggestions.
  • Perceived helpfulness of food scanning.
  • Perceived helpfulness of the voice interaction assistant.
  • Perceived helpfulness of insights provided by the AI assistant.
  • Overall satisfaction with the app.
Procedure

PROCEDURE

Survey Structure

5

Demographic

2

Preference

8

User Goal and Usage

Questions

Demographics / Preferences

1

Gender

2

Age

3

Frequency of Storing Food in the Fridge (past month)

4

Frequency of Finding Expired Food in the Fridge

5

Frequency of Cooking

at Home

6

Difficulty Managing

Nutritional Value

7

Trust in AI Assistance

ai_fridge.jpg

Measurements - Helpfulness Level

1

Food Storage Listing

2

Expiration Alerts

3

Nutritional Suggestions

4

Recipe Suggestions

5

Food Scanning

6

Voice Interaction Assistant

7

Insights Provided By the

AI Assistant

8

Overall Satisfaction

Results

Results

Demographics and Averages

Linear Regression

Conclusion

Conclusion

Average Helpfulness/

Satisfaction Ratings:

  • Range: 3.66 – 4.28 ✅

Linear Regressions:

  • Low correlation

  • Negative slopes: 4 (food scanning, expiration alerts, recipe suggestions, nutrition suggestions)

  • Positive slopes: 3 (food listing, AI assistance, AI voice)

  • Some individuals had high ratings for food/nutrition related issues vs. low-medium ratings for helpfulness or satisfaction of features

joseph-gonzalez-fdlZBWIP0aM-unsplash.jpg

Limitations

  • Prototype

    • Basic structure and minimal interactions

    • No actual AI implementation

    • No screen-reading/accessibility capabilities

  • Testing environment

    • Not an accurate environment

    • Demo video only, no interaction or tasks

Citrus Fruits

Next Steps

  • Interview survey participants

    • High ratings for food/nutrition related issues vs. low-medium ratings for helpfulness or satisfaction of features

  • Interview visually impaired and blind individuals

  • Refine prototype

    • Further develop Figma prototype

    • Incorporate AI or better mimic AI features

    • Incorporate or mimic screen-reading/accessibility features

  • User testing

    • Create and conduct user tests on refined prototype

  • Further statistical analysis using new data

Our Team

Our Team.

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