ReLoop

Inspiration

Recycling is often seen as inconvenient, unclear, and unrewarding, especially for the youth who want to take climate action but don’t know where to start. Inspired by apps that gamify good habits, ReLoop was created to transform how people see waste.

What it does

ReLoop is a mobile app that lets users scan recyclable items using their phone camera, get instant classification, and find nearby drop-off locations. After validating their drop, users earn EcoCoins, which can be redeemed for digital rewards, real-world discounts, or donations.

How we built it

We designed the UI/UX in Figma.

Challenges we ran into

Designing a seamless scan-and-reward loop without overcomplicating the visuals.

Accomplishments that we're proud of

Validated our idea with survey data from 100+ users.

What we learned

The simpler the flow, the higher the impact.

What's next for ReLoop

Integrate AI-powered image recognition for smarter item detection.

Please share a link to your interactive prototype. Make sure it's something we

can test or explore — not just a design file! https://www.figma.com/proto/3IfuOopwmAQPRRXAlU5MNl/ReLoop?node-id=43-145&t =ZElOAIYNfPrA5hRC-1&scaling=scale-down&content-scaling=fixed&page-id=0%3A1& starting-point-node-id=1%3A3&show-proto-sidebar=1

Give us a quick summary of your project. What does it do, and what problem

does it aim to solve? (max 150 words) ReLoop is inspired by the philosophy of gamification to make practicing and learning recycling rewarding, accessible, and fun. Users scan their waste with their camera, and are led to the nearest verified drop-off location. Once their waste has been collected, users earn ECoins, which can be redeemed in the in-app marketplace for real rewards or donations. ReLoop address the core issues of modern urban waste management: lack of motivation, confusion, and youth disengagement. By turning seemingly “boring” activities to a daily practice via action-reward system, it promotes individuals to take action without needing land or time.

Walk us through how you approached your research. Did you run any surveys

or interviews? If so, please link to your questions or forms. If you used online sources, include the links. Tell us what you discovered! (max 300 words) To ensure ReLoop was built around real user needs, I used a research-first approach via quantitative surveys, interviews, and secondary research from industry reports. I distributed a Google Form to over 100 individuals aged 16–30 (https://forms.gle/EPZwxdKFwN9ARnPHA ), focusing on urban Gen Z and Millennials. Key questions like, “What prevents you from recycling more?” revealed that 71% did not know what was recyclable, 87% said they felt they recycle less than they should, and 92% said they’d recycle more if rewarded with points or perks. These results were put into ReLoop’s reward-system, and camera scanning system. I also performed interviews with 7 users in different cities. Participants described recycling as “confusing” and “inconsistent." They also expressed interest in gamified apps, citing Duolingo and Fitbit as examples. I also reviewed the following publishments: https://www.epa.gov/facts-and-figures-about-materials-waste-and-recycling https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-circularity https://www.ellenmacarthurfoundation.org/topics/cities/overview These sources confirmed broader trends in recycling inefficiency and the need for decentralized, behavior-driven solutions.

What were the most impactful design choices you made, and why? Explain how

your research findings or user testing informed these decisions. (max 300 words) One of the most impactful design choices we made was centering the user experience around a camera-based scan-and-reward flow. This decision was directly informed by both our survey data, which highlighted that users felt overwhelmed by the complexity of recycling guidelines. In our survey (n=100+), 71% of respondents said they were unsure what items were recyclable, and over 50% admitted they had thrown away recyclables out of confusion or inconvenience. In follow-up interviews, users described recycling as “unclear” and “time-consuming.” By using image recognition and AI, ReLoop can automate the process of identifying an item’s material type, making the act of recycling easy. This feature directly increases user confidence. Additionally, our research showed that 92% of users were more likely to recycle if they received tangible rewards. That insight shaped our second major design decision: implementing instant ECoins rewards paired with positive feedback screens. Through testing, we found that these micro-incentives created a powerful sense of satisfaction and helped encourage habit formation.

Built With

• figma