Smart Waste Segregation and Gameification

Our AI waste sorter automates recycling, cutting landfill waste and promoting sustainability. With an educational web game, it boosts awareness of proper waste disposal to fight climate change.

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Smart Waste Segregation and Gamification

Inspiration

The staggering reality of waste management drove us to action:

  • $200 billion spent annually on waste management
  • 292.4M tons of municipal solid waste generated yearly
  • 4.9 pounds of waste per person per day
  • Only 69 million tons recycled vs 146.1 million tons landfilled

We saw an opportunity to make waste management both automated and educational, transforming a daily chore into an engaging learning experience.

What it does

Our project combines two innovative components:

  1. Smart Waste Sorter:

    • Uses computer vision (BLIP) to identify waste items in real-time
    • Automatically opens the correct bin using servo motors
    • Classifies items into E-Waste, Compost, or Recyclable categories
    • Provides instant feedback on waste categorization

  2. Educational Game:

    • Space Invaders-style gameplay
    • Players catch falling items matching waste categories
    • Real-time scoring system tracks environmental impact
    • Interactive controls via Arduino joystick

How we built it

Our system combines hardware and software components:

Hardware Components

  • Raspberry Pi with camera module
  • Arduino Uno/Nano/Pro Mini
  • Three servo motors (GPIO 26, 27, 22)
  • Analog joystick
  • Recycled Einstein Bros. boxes for bins

Software Implementation

  1. Waste Sorter Setup:
# Install requirements
pip install torch torchvision transformers opencv-python pillow RPi.GPIO

Run detector

python detector.py
  1. Game Setup:
# Clone repository and setup
git clone https://github.com/Girish-Krishnan/Smart-Waste-Segregation-And-Gamification
cd waste-game
chmod +x setup.sh
./setup.sh

# Start game server
python3 main.py

# Start Arduino controller
python3 arduino_controller.py


# Access game
http://localhost:5000
  1. Arduino Configuration:
  2. Connect joystick: X-axis → A0, VCC → 5V, GND → GND
  3. Upload arduino_sketch/waste_controller/waste_controller.ino

Technology Stack

  • BLIP image recognition model
  • Python backend
  • OpenCV for camera processing
  • Arduino for game controls
  • Web interface for game display

Challenges we ran into

  1. Hardware Integration:

    • Coordinating multiple GPIO pins
    • Achieving reliable camera processing
    • Calibrating servo movements
    • Syncing Arduino controls

  2. Software Development:

    • Optimizing BLIP model performance
    • Managing real-time processing
    • Handling classification edge cases
    • Creating smooth game mechanics

  3. Physical Construction:

    • Building sturdy bins from recycled materials
    • Mounting electronics securely
    • Ensuring reliable operation

Accomplishments that we're proud of

  1. Built a working prototype using sustainable materials
  2. Successfully implemented real-time waste detection
  3. Created an engaging educational game
  4. Achieved reliable sorting automation
  5. Developed a comprehensive waste classification system
  6. Integrated hardware and software seamlessly

What we learned

  1. Technical Skills:

    • Computer vision implementation
    • Hardware-software integration
    • Real-time system coordination
    • Game development principles

  2. Environmental Impact:

    • Waste management challenges
    • Recycling best practices
    • Sustainable design approaches

  3. Project Management:

    • Cross-disciplinary collaboration
    • Iterative development
    • Problem-solving strategies

What's next for Smart Waste Segregation and Gamification

  1. Technical Enhancements:

    • Custom-trained waste detection model
    • Enhanced classification accuracy
    • Multiple camera support
    • Mobile app development

  2. Feature Additions:

    • NFC-based reward system
    • Additional waste categories
    • Multiplayer game modes
    • Cloud data analytics

  3. Community Impact:

    • School implementation programs
    • Public space installations
    • Waste reduction tracking
    • Environmental impact metrics

We envision scaling this solution to revolutionize waste management education and automation across communities worldwide.

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