IoT Compost Bin
FoodPrint is a compost bin management idea designed to help Gen Z with the food waste composting process.
Work Type
Case Study
Time:
2023 Summer
Contributors:
Jerry Cai
Cherry Hu
Sunniva Long
Claire Li
My Role
UX Design
UI Design
Research
Prototyping
Backgrounds
We partnered with the LA Green New Deal, an initiative by the City of Los Angeles aimed at advancing sustainability and environmental action across local communities. Our goal was to design an innovative IoT composting solution specifically tailored to engage and empower Gen Z in making composting an accessible and meaningful part of their daily lives.
Problem Statement
How might we encourage Gen Zers (18+) to regularly compost their
food waste?
What is Composting?
Composting is the natural process of recycling organic waste, such as food scraps, into nutrient-rich fertilizer that benefits the environment.
Through Research We discover that …
Young users struggle with getting started and maintaining consistent habits.
Feel uncertain about the composting process and its effectiveness
Our Solution
A smart compost bin app that transforms the composting experience into a time-efficient and enjoyable activity for Gen Zers.
Home
Compost Bin Management
Real-time updates, visual compost progress tracking, and user-friendly guidance accommodate various lifestyles
Community
Give and Take
Easy reach out locals communities for free composting materials and donate surplus compost with the community
Research
Secondary Research
Understanding Compost in Current Society
“Students interested in gardening are influenced by older relatives, or personal involvement with organization/school club.”
Secondary Research
After gaining an initial understanding of the current challenges with composting, we begin attending site visits and workshops to learn more about the process and various composting methods.
Target User Interviews
We conducted interviews with a group of 9 participants to understand user behaviors, needs, motivations, and pain points. By learning and observing what stood out during these in-depth user interviews, we gained valuable insights from our participants.
Affinity Mapping
We synthesized the data from 9 user interviews into an affinity map to develop insights that are valuable and inspiring for our challenge.
We categorizing all the insights on our affinity map, we then use to transform into potential opportunities. By pursing discussion and voting, we develop our focus.
Problem Statement
How might we encourage Gen Zers (18+) to regularly compost their food waste?
User Type Research
We conducted interviews with a group of 9 participants to understand user behaviors, needs, motivations, and pain points. By learning and observing what stood out during these in-depth user interviews, we gained valuable insights from our participants.
Ideation Brainstorm
After conducting in-depth research, we identified five major features that address the problem. To receive feedback from users, we set up five tasks for them to complete and simulated the circumstances, allowing us to refine the design and user flow.
Main Features
Setup Compost Bin
Add in Greens
Away Mode
Give & Take
Away Mode
Prototype and User Test
User test and Design Iterations
We utilized a low-fidelity paper prototype UI and a physical device model to simulate the process of using the app and the compost bin. Testers were given different tasks to complete using the app, and by conducting this real-world experiment, we were able to identify issues, uncover accessibility gaps, and iterate on our design.
Problems we discovered through user testing
1. Anti-mapping of the drawer and the status bar of the ingredients on the landing page
2. User was confused by the status bar shown without consistent visual language
3. Users puzzled by the icon for adding materials without accompanying
4. textStatus bar category should be grouped with the bin instead of the current status
1. Forum screen overwhelms with excessive information
2. Information for give and take, guidance needed
3. Distinction between Forum and Q&A features is unclear, making it difficult to discern the difference
4. Chat-style forum discussion ineffective, better on computers
5. Search pop-up for recommendation and guide answers
Design System
