Overview

Greenergy is a mobile application designed to help users understand the environmental impact of their food choices. Using image recognition and machine learning, the app identifies food items and instantly visualizes their carbon footprint in a clear, approachable way.

This project was completed as part of the University of Washington Information School capstone, where our team of four (two designers, two developers) was challenged to plan, design, document, and build a solution to a real‑world problem.

Problem Statement

Most people want to make environmentally conscious choices, but carbon footprint data is difficult to understand and rarely accessible at the moment of decision. Users needed a simple, immediate way to understand the environmental impact of everyday food items.

How might we help people quickly understand the carbon impact of their food choices so they can make more environmentally conscious decisions?

Research

To understand how food choices relate to climate change and how users perceive this connection, our team conducted user research, market research, and a literature review. Our goal was to identify gaps in awareness and opportunities to present carbon‑impact information in a simple, accessible way.

User Research

We focused on people who were generally unaware of the relationship between food consumption and climate change. Using surveys and interviews with friends, family, and peers, we explored:

• Whether users knew that food choices contribute to greenhouse gas emissions

• How often they consumed high‑impact foods such as red meat

• What motivated or discouraged them from making environmentally conscious decisions

This helped us understand baseline awareness and identify opportunities for clearer, more immediate feedback.

Market Research

We analyzed existing apps and services related to sustainability, food tracking, and carbon footprint awareness. Our goal was to understand:

• How competitors presented environmental data

• What features users found helpful or overwhelming

• Where current tools failed to provide quick, actionable insights

This revealed a gap: most tools required manual input or presented data in complex formats that were difficult to interpret.

Literature Review

To ground our design in accurate environmental data, we reviewed academic and industry research on:

• The carbon footprint of common foods

• How different food categories compare in greenhouse gas emissions

• Methods for assessing and reducing personal carbon impact

This helped us build a foundational understanding of which foods contribute most to emissions and how to translate that information into user‑friendly visualizations.

Research Insights

Our research revealed several behavioral, market, and technical insights that shaped the direction of our project. These insights helped us understand user awareness, identify gaps in existing tools, and determine the feasibility of building an image‑recognition–based carbon‑footprint experience.

Our Solution

Personas

To guide our design decisions and ensure we were addressing real user needs, we created three personas representing individuals who care about the environment but lack a deep understanding of how their food choices contribute to climate change. These personas helped us stay focused on user motivations, behaviors, and pain points as we mapped out the product experience.

User Journey Map

This journey map illustrates how each persona moves from choosing food to becoming aware of its environmental impact. It highlights their motivations, pain points, and opportunities for Greenergy to support their goals.

Low-Fidelity Prototype

Design System

After establishing the structure through low‑fidelity wireframes, our next step was to define the visual direction for Greenergy. We focused on selecting colors, typography, and UI components that aligned with our theme of environmental awareness and carbon‑impact education.

We decided to use colors that went with a theme that spoke sustainability, reduction, and environmental clarity.

For typography, we selected simple typefaces to maintain readability and ensure that the carbon‑impact information remained the focal point. The goal was to create a clean, modern aesthetic that supports accessibility.

We put in other components, such as images, assets, buttons, and icons to build our “moodboard” to build a general feel of how the product should look.

High-Fidelity Prototype

With our visual direction established, we moved into creating the high‑fidelity prototype. This stage focused on bringing together our finalized color palette, typography, imagery, and UI components to create a cohesive and realistic representation of the Greenergy experience.

Impact

Through this project, we created a solution that helps users understand the environmental impact of their food choices in a simple, accessible way. By combining machine learning–based food recognition with intuitive carbon‑impact visualizations, Greenergy makes sustainability information available at the exact moment users need it.

Our usability testing showed that:

• Users became more aware of how everyday foods contribute to carbon emissions

• Visual indicators and comparisons helped users interpret complex data quickly

• Participants felt more motivated to make lower‑impact choices over time

• The app encouraged reflection without guilt, supporting positive behavior change

• ~15% reduction of carbon footprint in users

Overall, Greenergy demonstrated how thoughtful design can make sustainability education more approachable and actionable.

Reflection

Our team set out with a simple but ambitious goal: to create something that could make a meaningful, positive impact on the world. By designing a tool that helps people understand how their food choices affect their carbon footprint, we created an experience that is both innovative and educational. If users become more aware of the environmental impact of what they eat, they may feel empowered to make small lifestyle changes that contribute to a healthier future. Greenergy was built to support that feedback loop by helping users learn, reflect, and reduce their carbon impact over time.

Working on this project also reinforced the importance of strong collaboration. I had worked with several teammates before, so I expected that we would communicate well and produce something we were proud of. Those expectations were met. Despite the challenges of Covid‑19, which prevented us from meeting in person, we adapted quickly. We held frequent online meetings, kept each other accountable, and supported one another through each stage of the process. This experience reminded me how essential communication, flexibility, and shared ownership are in creating a successful product.

Overall, this project strengthened my ability to design with purpose, collaborate effectively, and adapt to unexpected constraints — all while working toward a solution that encourages positive environmental change.

Continuation & Improvements

While Greenergy successfully introduces users to the carbon impact of their food choices, there are several opportunities to expand the product and deepen its long‑term value.

1. Expand and diversify the food database

To improve accuracy and relevance, I would integrate a broader dataset that includes:

• More global and culturally diverse foods

• Packaged items using barcode or nutrition‑label scanning

• Regional variations in carbon impact

A richer dataset would make Greenergy more useful in everyday decision‑making.

2. Improve machine‑learning performance

As more users interact with the system, the model could be retrained to:

• Better recognize mixed dishes and complex meals

• Reduce misclassifications

• Improve speed and confidence scoring

This would create a smoother, more reliable experience.

3. Introduce personalized insights and goals

To support long‑term behavior change, I would explore features such as:

• Weekly summaries of carbon savings

• Personalized recommendations based on eating patterns

• Optional goals like “Reduce your footprint by 10% this month”

These features would help users stay engaged and see their progress over time.

4. Explore real‑world integrations

Partnerships could extend Greenergy beyond the app, allowing users to:

• Scan grocery items or menus

• Discover sustainable restaurants

• View carbon‑impact labels in real time

This would bring sustainability awareness directly into users’ daily routines.

5. Add community and social features

For users like Lisa, social influence is a powerful motivator. Future iterations could include:

• Sharing sustainable meals

• Gamification of milestones (badges)

• Participating in challenges or community goals

This could amplify impact and increase engagement.

6. Conduct long‑term evaluation

To understand Greenergy’s real impact, I would run:

• A/B tests on visualizations

• Surveys on behavior change over time

This would help validate whether the product truly shifts habits and awareness.