Yenn

Identifying the Awareness Gap Behind Household Food Waste

To understand how and why people waste food at home, I began by exploring behavioral patterns in leftover management. According to the EPA and MITRE–Gallup (2023), approximately 80% of Americans discard edible leftovers every week, largely due to forgetfulness and uncertainty about food safety.

I conducted contextual inquiries and interviews with university students and young professionals who frequently cook at home. The findings highlighted recurring challenges:

Key Insights

• Forgetting leftovers: Users rarely remember what’s hidden behind new groceries.

• Trust and safety doubts: Many rely on smell or appearance rather than expiration data.

• Ingredient-first cooking: People pick what looks usable, then search for matching recipes.

• Over-cooking: Guessing portions creates new leftovers, continuing the cycle.

User Quote: “I always tell myself I’ll use what’s in the fridge… then I find it moldy two weeks later.”

Research Conclusion: Household food waste stems from an “awareness-to-action gap”. Users know what’s in their fridge but lack timely reminders or creative ideas to use it before it spoils.

This discovery led to YENN’s design goal:
Transform the refrigerator into an intelligent assistant that helps users see, remember, and creatively use what they already have.

Designing an AR-Assisted Decision Moment at the Refrigerator

My design strategy emerged from the research insights. I focused on augmenting natural cooking behavior rather than changing it.

Design Objectives

1. Seamless Awareness
YENN should recognize fridge contents automatically through an AR-enabled camera view, turning visual inventory into immediate meal ideas.

2. Just-in-Time Support
The system should surface recipes and spoilage cues at the exact moment users open the fridge, when decisions are made.

3. Sustainability Feedback
Provide visible, rewarding insights into how much food, money, and CO₂ the user saves by cooking leftovers instead of wasting them.

System Approach

Using a systems-thinking framework, I mapped relationships between users, food storage habits, and sustainability goals. The experience focuses on two key intervention points:

• Post-meal storage: When leftovers are placed in the fridge.

• Meal planning: When users decide what to cook next.

Targeting these phases allows YENN to close the feedback loop between storage and reuse, helping users act before food spoils.

Simulating AR Ingredient Recognition and Just in Time Recipe Support

I translated our design strategy into a functional proof-of-concept prototype built in Figma.
The prototype simulates the core AR flow by scanning fridge contents, recognizing items, and suggesting recipes instantly.

1. AR-Based Scanning

When users open the fridge, they point their phone at it.
YENN automatically:

• Detects and labels ingredients with bounding boxes.

• Displays freshness indicators (Safe, Soon, Expiring).

• Suggests 2–3 recipes using the selected items.

2. Smart Expiry Notifications

Users receive subtle reminders when ingredients are about to expire.
The system tracks items over time, notifying users only when action is needed, preventing waste without overwhelming them.

3. Interface & Visual Language

• A soft green and neutral palette communicates freshness and sustainability.

• Simple, card-based layouts minimize cognitive load.

• The Rewarding Dashboard visualizes users' zero-waste streaks and reward badges.

Technical Feasibility

At this stage, I focused on “role” and “look-and-feel” testing, validating concept desirability before investing in complex computer-vision models. The prototype demonstrates interaction timing and user trust during the fridge-open decision moment.