RecycleX

Turn Waste into Worth, One Click at a Time!

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Inspiration

With increasing waste pollution and a lack of structured recycling systems, we wanted to create a platform that encourages sustainable waste management. Many recyclable items end up in landfills due to a lack of awareness and accessibility to proper recycling channels. Our goal was to bridge this gap by providing an AI-powered marketplace where users can identify recyclable materials and connect with buyers.

What it does

RecycleX is an education-first web application that helps users:

  • Identify recyclable items using computer vision.
  • Provide insights into material sustainability, estimated market value, and carbon emissions saved.
  • Connect sellers of recyclable materials to nearby buyers.
  • Offer learning resources to promote better recycling habits.

How we built it

  • Frontend: Built with Next.js and TypeScript for a fast and scalable user experience.
  • Backend: Utilizes Next.js API routes, Prisma ORM, and a PostgreSQL database hosted on NeonDB.
  • AI Integration: Gemini AI for material classification and analysis, providing sustainability scores, market demand, and carbon footprint savings.
  • Authentication: Implemented using Clerk for secure and seamless user management.
  • Geolocation Services: Uses OpenCage API to auto-fill user locations and match them with the nearest buyers.

Challenges we ran into

  • AI Accuracy: Ensuring the model correctly identifies materials and provides accurate sustainability insights.
  • Buyer-Seller Matching: Implementing a matching algorithm that efficiently connects sellers with nearby buyers based on material type and location.
  • Geolocation Limitations: Handling permissions and accuracy issues with location services.
  • Scalability: Structuring the database and API endpoints to handle a growing number of users and transactions.

Accomplishments that we're proud of

  • Successfully integrating Gemini AI to analyze uploaded images and generate structured data.
  • Implementing a real-time marketplace for recyclable materials.
  • Providing users with a clear environmental impact by estimating carbon emissions saved.
  • Ensuring a smooth and intuitive user experience with Next.js and Clerk authentication.

What we learned

  • Optimizing AI models for real-world recycling applications.
  • Efficiently using geolocation services to enhance user experience.
  • Implementing best practices for matching buyers and sellers in a marketplace model.
  • The importance of user education in making recycling a sustainable habit.

What's next for RecycleX

  • Expand Material Recognition: Improve AI accuracy by training on a larger dataset.
  • Enhanced Buyer-Seller Matching: Implement a recommendation engine to suggest the best buyers based on price, proximity, and demand.
  • Gamification & Rewards: Introduce incentives for users to recycle more by tracking their contributions and rewarding them.
  • Mobile App Version: Expand accessibility by developing a mobile app for on-the-go recycling.
  • Integration with Local Recycling Centers: Partner with recycling centers to offer pick-up services and better price estimates.

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