A 0→1 product built from concept to real-world use
AI-Powered Food Management App for Reducing Household Food Waste

Role
Project lead · Research Lead · UX Design · Prototyping
Overview
AvoMate is an AI-powered food assistant that tracks ingredient freshness, sends timely reminders, and suggests recipes based on what users already have, helping reduce food waste in a simple, practical way.
As the Project Lead, I led the end-to-end design, focusing on how AI can support quick, everyday decisions in the kitchen. This project strengthened my ability to design intuitive user experiences and simplify complex systems into easy-to-use interactions.
Timeline
Jan - Mar 2025
Team
Shan Huang
Yuqi Cao
Tools
Figma, Miro, Photoshop, After Effects

Goal Statement
To design and validate a mobile application within 70 days that helps households earning less than $50,000 to 100,000 annually reduce food waste, with the potential to save approximately $728 per person per year.
Outcome
Improved ingredient visibility and reuse behaviors
Food waste
Potential savings of $728
per person per year
Cost awareness
Validated low-effort workflows
for busy households
Everyday usability
Design Process

Smart Inventory Input
Turn ingredient tracking into a fast and effortless experience
Scan receipts to automatically extract and add items
Capture photos to recognize and log ingredients instantly
Manually input items with a quick and simple flow
Freshness Insights & Recommendations
Turn everyday cooking decisions into clear, actionable insights
Quickly review ingredient freshness and prioritize what to use first
Highlight near-expiring items with urgency cues and suggested actions
Discover recipes based on available ingredients
Keep inventory up to date with minimal effort
Swipe to quickly remove items
Tap to edit ingredient details and remaining quantity
Savings & Impact Visualization
Make mindful cooking measurable and rewarding
Track waste reduction and money saved
Turn small daily actions into visible long-term impact
Where our waste comes from:
40%
restaurants, grocey stores
16%
farms
2%
manufactures
43%
homes
Why does household food waste matter?
Food waste = Emissions
Wasted food =
100M CO₂
1.13M methane
52–59% of households
earning less than $50,000 to 100,000 annually think reducing food waste is "Very important"
Source: U.S. EPA — Estimating the Cost of Food Waste to American Consumers
12
Interviewees
344
Data points
01 Everyday mental load makes it difficult for users to consistently manage their food.
02 Although users want to reduce waste, they often forget what they have and fail to act in time.
03 Users rely on subjective judgment of freshness, resulting in missed opportunities to use food before it spoils.
Voice of The Customers
We surveyed 74 participants across varied income groups. Results revealed strong demand for automated input, freshness reminders, ingredient-based recipes, and savings feedback, highlighting the need for low-effort, time-sensitive support in everyday food management.




Problem Statement

01
Real-time ingredient tracking

1

Carrot expiring soon!
2
02
Freshness-based reminders

3
03
Recipe based on ingredients

4
04
Daily food management
Model Experience

Competitive Analysis
Most competitors focus on recipes or isolated tools, assuming users plan meals in advance. In reality, people forget what’s in their fridge, rely on subjective freshness cues, and miss the right moment to act, turning good intentions into unnecessary food waste.

Who is going to use the service
Persona

Mario(26) She / Her / Hers
New York
Independent designer with a busy work schedule
“I wish I could waste less food by managing my food more effortlessly.”
Bio
Maria is a 26-year-old independent designer based in New York.
She has a busy, unpredictable schedule balancing work and personal life. Meals are often quick decisions with little time to plan.
Painpoints
Often forgets what’s in her fridge, leading to ingredients going bad.
Feels overwhelmed when deciding what to cook after a long day.
Goal
Reduce food waste while simplifying everyday decision-making
User Journey Map
By mapping user behaviors and data integration across each stage, we identified key friction points and opportunities in daily cooking decisions.

From Sketches to High-Fidelity Design
Design Development
Wireframe
Here are my initial wireframe explorations based on research insights and user needs. These early sketches helped visualize core flows.

Mid-Fidelity
These mid-fidelity wireframes refine layout structure, user flows, and interaction patterns to validate key usability decisions.

Usability Testing
I conducted usability testing with 18 target users to evaluate whether AvoMate’s inventory tracking and recipe features could help reduce food waste and support quicker cooking decisions.


User satisfaction improvement on Inputting Ingredients
28%
Ingredient freshness track rating
4.6/5
Recipe recommendation Rating
4.5/5
Design Iteration
Through usability testing and feedback, the following key improvements were made across inventory, freshness tracking, recipe customization, and profile experience.

Ingredient list felt dense and text-heavy
Freshness status wasn’t immediately clear
Expiring items lacked visual priority

Ingredient list felt dense and text-heavy
Freshness status wasn’t immediately clear
Expiring items lacked visual priority

Freshness graphs lacked clear hierarchy
Excess secondary info increased cognitive load
Suggestions were buried under analytics

Added “Urgent” alerts with direct recipe access
Highlighted key symptoms as tags
Turned freshness data into actionable guidance

Users had to mentally match ingredients with recipes
Customization required too many steps

Prioritized recipes based on available ingredients
Enabled quick recipe browsing simplified filters

Profile focused on settings
Personal impact wasn’t visible
No feedback loop for waste reduction

Created a visual feedback loop through Kitchen Impact metrics
Introduced time-based trends
Separated settings from personal performance
Manual Tracking
Smart Assistance
Interactivity
AvoMate

Passive
Interactive
Intelligent Guidance
Next Steps
Improve ingredient recognition (receipt + image accuracy)
Test long-term impact on behavior and food waste
Enhance personalization with user preferences and history
Explore integrations with smart devices and grocery platforms
Designing AvoMate reinforced that food waste is not a motivation problem, but a cognitive one, users lack visibility and timely cues in their daily routines.
This project taught me to design for real-life contexts, not just screens, and to prioritize clarity, action, and feedback over complexity. Through this process, I strengthened my ability to create behavior-driven experiences that reduce cognitive load and support more sustainable everyday habits.



