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🥕 ZeroHunger Connect: Bridging Surplus to Need

A Data-Driven Platform to End Food Waste and Insecurity

Our mission began with a clear purpose: to confront the paradox of local food waste occurring simultaneously with rising household food insecurity. We built ZeroHunger Connect to be the intelligent bridge—a seamless, efficient marketplace connecting local surplus directly to communities in urgent need.

This platform is custom-built to be intuitive for two distinct user groups and uses real-time data to drive impact.


✨ Key Features & Innovation

We made this project our own by implementing critical features and data infrastructure:

1. Two-Sided Dynamic Interface

The application starts with a clean Role Selection home page, giving users dedicated pathways:

  • Vendor Surplus Broadcast: Allows verified businesses to quickly input food details and quantity, instantly broadcasting their surplus for pickup.
  • Charity & Shelter Access: Provides a filtered feed and map view focused on claiming available donations and viewing high-need hotspot data.

2. Dynamic & Accurate Mapping

The application relies on dynamically loaded data, rather than static mock-ups, ensuring real-world accuracy:

  • Food Bank Locations: Locations for local food assistance organizations are loaded directly from a structured CSV source (clean_food_banks.csv).
  • Insecurity Heatmap: Hotspot data is loaded from a separate CSV (ontario_phu_percentage.csv), ensuring the visual map layer always reflects the latest, reliable household food insecurity statistics.

🚀 Run Locally

To get the application running on your machine, follow these steps.

Prerequisites:

  • Node.js (required for npm and the development server)
  • Git (required for version control)
  1. Install dependencies:
    npm install
  2. Configure API Key: Set the GEMINI_API_KEY in your .env.local file to connect the AI Assistant and Vendor suggestions.
    GEMINI_API_KEY=YOUR_API_KEY_HERE
    
  3. Start the app:
    npm run dev

The application will launch in your browser at http://localhost:3000.

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