Submission for KTHack 2025

Devpost: https://devpost.com/software/verda-edo7uq

• Trash Sorter: Uses AI to identify items via your camera and suggests the correct disposal bin based on regional guidelines, eliminating recycling guesswork.
• CO2 Calculator: Helps you estimate the carbon footprint of your daily activities.
• History: Tracks your trash scans, CO2 calculations, and AI recommendations over time, allowing you to monitor your progress in adopting sustainable practices.
• AI-Powered Quiz: Offers personalized guidance based on user responses, deepening understanding of sustainable practices.
• Ranking System: Allows users to track progress and see how they stack up against others, making eco-conscious habits engaging.

• HTML
• CSS
• Next.js
• Tailwind CSS
• Google Gemini API
• Google Teachable Machine
• Supabase
• React

To run Verda locally, follow these steps:

1. Clone the repository:

   git clone [your_repository_url_here]
   cd verda

2. Install dependencies:

   npm i
   npm install @supabase/supabase-js @teachablemachine/image @supabase/auth-helpers-nextjs
   npm install --save-dev @types/react @types/node

3. Set up environment variables: Create a .env.local file in the root of your project and add your API keys:

   NEXT_PUBLIC_GEMINI_API_KEY=YOUR_GEMINI_API_KEY
   NEXT_PUBLIC_SUPABASE_URL=YOUR_SUPABASE_URL
   NEXT_PUBLIC_SUPABASE_ANON_KEY=YOUR_SUPABASE_ANON_KEY
   

   • YOUR_GEMINI_API_KEY: Obtain this from the Google AI Studio or Google Cloud Console.
   • YOUR_SUPABASE_URL: Find this in your Supabase project settings.
   • YOUR_SUPABASE_ANON_KEY: Find this in your Supabase project settings.

4. Start the development server:

   npm run dev

5. Open http://localhost:3000 in your browser to see the application.

Did you know that 263.16 billion pounds of recyclable material are mis-sorted or not recovered every year in the U.S. alone? It's a staggering amount that highlights a major hurdle in our fight against climate change. We believe that empowering individuals with the right tools can make a monumental difference. That's why we created Verda—to transform confusion into clarity and enable everyone to be a part of the solution, right from their homes.

Verda drives real behavioral change by making environmental responsibility tangible. We raise awareness by helping users visualize their carbon footprint and waste habits. By tracking CO2 and waste, and providing country-specific suggestions for proper disposal and reduction, Verda helps users actively contribute to a greener planet.

To build Verda efficiently, we leveraged publicly available datasets and machine-learning models for the AI-powered trash sorter. We meticulously researched 20 countries' trash-sorting systems to provide individualized guidance. Google's Gemini 1.5 Flash model powers our AI recommendations and complex CO2 emission calculations, handling parameters that simple formulas couldn't. The ranking system was developed using a robust Supabase backend for accurate tracking and display.

Our most significant challenge was setting up and managing the database to handle the vast and varied information required for waste identification and precise, country-specific sorting rules. The diverse recycling guidelines across regions demanded extensive research and careful data structuring. We also dedicated considerable effort to designing an intuitive UI/UX that simplifies complex waste disposal decisions.

We are incredibly proud of Verda's smooth styling and intuitive user interface, which creates a seamless user experience. Getting the backend to work efficiently and reliably was a major accomplishment, ensuring our AI and data processing run smoothly. We are also thrilled with the engaging and educational experience provided by our AI-powered quizzes, which foster a deeper understanding of sustainable living.

Building Verda was a profound learning experience. We gained significant expertise in backend development, complex data structures, and seamless communication between components. We honed our skills in version control and deep-dived into frontend styling and user-centered design. We also mastered the intricacies of deployment on domains. Beyond technical skills, we learned extensively about global waste statistics and the diverse waste sorting systems in different countries.

For Verda, we envision integrating with hardware, specifically smart bins already being deployed in some regions, for a more automated experience. Our next major goal is to expand our database to include all countries worldwide, solidifying Verda as a truly global solution for waste sorting. We're excited to continue empowering individuals to make a tangible difference in waste management and sustainability.