Recycle AI

DIY things to make with the thing you took a pic of in results page
Initial Splash Page
Camera UI
Results Page
Locations in results page for where to recycle specialized items

About Recycle AI

The idea for Recycle AI stemmed from a simple realization: recycling can be unnecessarily complicated. Existing resources often leave users with more questions than answers and don't address the larger goal of building a circular economy. We wanted to change that by creating a tool that not only simplifies recycling but sparks a change in how people view their waste.

What it does

Recycle AI combines cutting-edge technology with a user-friendly design to streamline the recycling process and encourage more sustainable habits:

AI-powered image recognition: Users take a photo, and Gemini AI analyzes the image to identify the materials and offer clear disposal instructions. Location-based recycling suggestions: The app leverages Google Maps integration to pinpoint nearby recycling centers. DIY and upcycling inspiration: Recycle AI offers a curated selection of DIY videos and ideas, demonstrating the potential to give items a second life.

How we built it

Gemini AI: This forms the core of our image recognition capabilities. Google Maps API: Provides the framework for our location-specific search functions. Frontend development: We prioritized an intuitive mobile-first design with a focus on a familiar user experience.

Challenges we ran into

Image recognition accuracy: Training the AI model on a wide range of materials and complex packaging required significant refinement. DIY content curation: Sourcing high-quality, relevant upcycling content was an ongoing effort. Operating on a limited budget: We relied extensively on open-source tools and creative workarounds.

Accomplishments that we're proud of

User-centric design: Early feedback underscores the success of Recycle AI's intuitive and accessible interface. Innovative AI application: We effectively harnessed Gemini AI to address a practical, real-world problem. Fostering a sustainable mindset: Our commitment to promoting reuse and upcycling sets us apart in this space.

What we learned

The value of iterative design: Constant testing and refinement of both the AI model and user interface was essential. The potential for technology-driven sustainability: Recycle AI demonstrates how AI can drive positive environmental action. The importance of a holistic approach: Effective waste reduction goes beyond recycling and encompasses reuse and upcycling.

What's next for Recycle AI

Expanding our knowledge base: We aim to continually improve the accuracy of our AI image recognition model. Building a community: We envision adding features that allow users to share and exchange upcycling ideas and materials. Strategic partnerships: Collaborations with recycling facilities and sustainable businesses will further our reach and impact.