Ever stood in front of three different bins, holding a piece of trash, and thought, “Where does this go?” 🤔 I did too, and that’s why I built a smart garbage separator that does the thinking for you!

In this post, we’ll build an AI-powered waste sorting system using ESP32, MicroPython, and Google’s Gemini API. It’s like having a recycling expert in your bin! 🗑️

⚡ Check out the project repository for the complete source code, detailed setup instructions, and to contribute to the project! Feel free to star the repo if you find it helpful. 🌟

Why Build a Smart Garbage Separator?

  • Automated Sorting: No more guesswork about where trash belongs
  • Better Recycling: Reduce contamination in recycling streams
  • Educational: Learn about IoT, computer vision, and mechanical systems
  • Fun Project: Combine hardware, software, and AI in one build

⚡ While commercial waste sorting systems cost thousands, we can build a working prototype for under $100!

What You’ll Need

Hardware Components 🛠️

  • Seeed Studio XIAO ESP32S3 Sense (the brain with built-in camera)
  • IR Sensor (the detector)
  • 4 Servo Motors (the sorters)
  • Stepper Motor (the conveyor)
  • 16x NeoPixel LED Ring (to light up the waste for better camera visibility)
  • 4x20 LCD Display (the informer)

Skills Required 🎯

  • Basic Python programming
  • Simple soldering
  • Understanding of GPIO pins
  • Experience with I2C and PWM protocols

The Build Process

Step 1: Hardware Setup

First, let’s connect everything according to this pinout:

# Key pin configurations
SERVO_PINS = {
    'front_1': 9,    # Front sorting mechanism
    'front_2': 8,    # Front sorting mechanism
    'drop_1': 7,     # Drop mechanism
    'drop_2': 44     # Drop mechanism
}

SENSOR_PINS = {
    'ir': 41,        # Object detection
    'neopixel': 1,   # Status indication
}

STEPPER_PINS = {
    'in1': 2,        # Stepper motor control
    'in2': 3,        # Stepper motor control
    'in3': 4,        # Stepper motor control
    'in4': 43        # Stepper motor control
}

I2C_PINS = {
    'sda': 5,        # LCD data line
    'scl': 6         # LCD clock line
}

Think of this pinout as a recipe for connecting all our components. Each pin has a specific job, just like ingredients in a recipe! 🧩

Step 2: The Magic Code

Here’s the main control loop that makes everything work:

async def main_loop():
    while True:
        if ir_sensor.detect_object():
            # Capture image
            image = camera.capture()
            
            # Classify waste
            category = await classify_waste(image)
            
            # Sort waste
            await sort_waste(category)
            
            # Update display
            lcd.show_status(category)
            
            # Indicate success
            neopixel.show_success()

This code is like a well-choreographed dance! 🕺 Each component plays its part:

  • The IR sensor spots the waste (like a bouncer at a club)
  • The camera takes a photo (our AI’s eyes)
  • Gemini API identifies the waste (the brain)
  • Stepper motor moves it along (the conveyor)
  • Servos drop it in the right bin (the hands)
  • LCD and NeoPixels give feedback (the voice)

How It Works

  1. Detection: IR sensor spots incoming waste
  2. Imaging: Camera captures the item
  3. Classification: Gemini API identifies the waste type
  4. Sorting: Servos direct the item to the right bin

It’s like having a tiny recycling expert inside your bin! 🧠

Project Structure

Garbage-IoT/
├── Garbage-Separator.py    # Main application code
├── neopixel_driver.py      # NeoPixel LED control
├── motor.py                # Stepper motor control
└── machine_i2c_lcd.py      # LCD display control

Each file has its own superpower! 🦸‍♂️

Challenges and Solutions

🎯 Challenge 1: Real-time Processing

The ESP32’s limited processing power made real-time image analysis challenging.

Solution: Optimized image capture and processing routines.

🎯 Challenge 2: Mechanical Reliability

Servo motors needed precise timing.

Solution: Implemented a state machine for reliable motor control.

🎯 Challenge 3: Power Management

Multiple motors and sensors required careful power management.

Solution: Added power monitoring and sleep modes.

Every challenge is just a puzzle waiting to be solved! 🧩

Project Final Photo

📸 The completed smart garbage separator in action

Final Project

Troubleshooting Tips

  • Camera not working?
    → Check power supply and I2C connections

  • Servos acting weird?
    → Verify PWM frequency and duty cycle

  • WiFi issues?
    → Double-check credentials and signal strength

Remember: Every bug is just a feature in disguise! 🐛

Useful Links

Project Evolution and Next Steps

While this project has reached a stable state, here are some potential areas for future development:

  • Weight Sensors: Adding weight sensors could improve categorization accuracy
  • Mobile App: A companion app for monitoring and control
  • On-device ML: Implementing machine learning directly on the ESP32S3
  • Analytics: Adding waste composition tracking and reporting

The future is full of possibilities! 🚀

Built with ❤️ and a lot of coffee ☕