Dooki Reverse Vending Machine

Inspiration

Recycling in Singapore is hindered by inconvenience, contamination issues, and lack of tangible incentives, leading to low participation rates and wasted resources. Inspired by the need to align with Singapore’s Zero Waste Masterplan, we wanted to create a solution that makes recycling simple, rewarding, and community-driven, encouraging households to build sustainable habits.

What it does

The Dooki Reverse Vending Machine:

Uses AI to identify recyclable materials and detect contamination. Tracks contributions by household via Singpass integration. Rewards users with tangible incentives like utility bill savings. Paired with an app, it lets households track progress, celebrate milestones, and compete in neighborhood recycling challenges.

How we built it

Hardware: Sensors for material detection, AI-powered cameras for contamination checks, and a modular design for easy deployment. Software: Machine learning models for material recognition, Singpass integration for user authentication, and a backend system to log household contributions. App: Tracks recycling data, rewards progress, and engages users with gamified challenges.

Challenges we ran into

Hardware challenges, the ESP32 didn't work as intended

Accomplishments that we're proud of

Building a prototype that has AI, hardware, and app integration. Creating a user-friendly system that directly incentivizes recycling while promoting community participation. Designing a solution that aligns with national sustainability goals and encourages long-term behavior change.

What we learned

The importance of user-centric design in encouraging adoption of sustainability solutions. Technical insights into AI-based material recognition and contamination detection. The value of integrating incentives with everyday systems like utility bills to drive participation.

What's next for Dooki Reverse Vending Machine

Pilot Deployment: Test machines in high-traffic locations like HDB estates and malls to gather user feedback. Expand Materials: Incorporate e-waste and textiles into the system. Community Engagement: Launch app-based recycling challenges and partnerships with schools to promote sustainability education. Data Insights: Use backend data to optimize machine placement and support policy-making for a greener Singapore.

Built With

• arduino
• autodesk-fusion-360
• edgeimpulse