Hand Gesture Recognition Traffic Control System

Project Overview

This project uses hand gesture detection with a webcam to recognize finger positions and control an Arduino-based LED and buzzer system. The system simulates a traffic signal/pedestrian detection system by interpreting different finger counts as traffic control signals.

Features

• 🤚 Real-time Hand Detection: Uses MediaPipe for accurate hand tracking
• 📹 Webcam Input: Real-time video feed processing with OpenCV
• 💡 LED Control: 5 LEDs controlled based on finger count
• 🔊 Buzzer Feedback: Audio alerts for hand detection and gestures
• 📡 Serial Communication: Arduino communication via USB/COM port
• 🚦 Traffic Signal Simulation: Different finger counts represent different signals

Hardware Components

Arduino Pins Configuration

Component	Arduino Pin	Description
LED 1	Pin 8	For 5 fingers (STOP)
LED 2	Pin 9	For 4 fingers (Pedestrian Lane)
LED 3	Pin 10	For 3 fingers (GO)
LED 4	Pin 11	For 2 fingers (Slow Down)
LED 5	Pin 12	For 1 finger (Warning)
Buzzer	Pin 6	Audio alert (1200Hz for hand detection, 500Hz for no fingers)

Finger Count Signals

Fingers	Signal	LED	Buzzer	Status
0	No one manage	OFF	500Hz (300ms)	Error state
1	Warning	LED at Pin 12	Silent	Caution
2	Slow Down	LED at Pin 11	Silent	Reduced speed
3	GO	LED at Pin 10	Silent	Safe to proceed
4	Pedestrian Lane Walking	LED at Pin 9	Silent	Pedestrian mode
5	STOP	LED at Pin 8	Silent	All stop

System Requirements

• Arduino Board (Uno, Mega, or compatible)
• Webcam (USB camera)
• Python 3.7 or later
• Windows, macOS, or Linux
• USB Cable (for Arduino communication)

Setup Instructions

1. Arduino Board Setup

1. Connect your Arduino board to your computer via USB cable
2. Open Arduino IDE
3. Select the board type: Tools → Board → Arduino Uno (or your board type)
4. Select the COM port: Tools → Port → COM4 (check which COM port Arduino uses)

2. Python Environment Setup

Option A: Using pip

# Navigate to the project directory
cd "C:\Users\Sam Nahutdo\Desktop\samnahutdo\MS101"

# (Optional) Create a virtual environment
python -m venv venv
venv\Scripts\activate  # On Windows

# Install required modules
pip install opencv-python
pip install mediapipe
pip install pyserial

Option B: Windows (Direct Installation)

If you don't have Python installed, download it from https://www.python.org/downloads/ and make sure to check "Add Python to PATH" during installation.

3. Arduino Code Installation

1. Open Arduino IDE
2. Open the sketch file: Arduino.cpp
3. Upload to Arduino:
   • Click Upload button (or Ctrl+U)
   • Wait for "Done uploading" message

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How to Compile and Run

Compiling C++ to Arduino Code

The Arduino.cpp file is already in the correct Arduino format. Here's how to compile and upload it:

1. Open Arduino IDE
2. File → Open → Select Arduino.cpp
3. Verify Code (Ctrl+R)
   • This compiles the code and checks for errors
4. Upload (Ctrl+U)
   • Compiles and uploads the code to the Arduino board
   • Wait for the message: "Avrdude done. Thank you."
5. Check Serial Monitor (Tools → Serial Monitor)
   • Set Baud Rate to 9600
   • Should show connection messages

Running Python Hand Detection

1. Open Command Prompt or PowerShell

2. Navigate to project directory:

   cd "C:\Users\Sam Nahutdo\Desktop\samnahutdo\MS101"

3. Activate virtual environment (if created):

   venv\Scripts\activate

4. Run the Python script:

   python main.py

5. What happens:

   • Webcam window opens with live hand detection
   • Green text = Hand detected
   • Red text = No hand detected
   • LEDs light up based on finger count
   • Press ESC to exit the program

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Module Installation Guide

Required Python Modules

# OpenCV - For video capture and image processing
pip install opencv-python

# MediaPipe - For hand landmark detection
pip install mediapipe

# PySerial - For Arduino communication
pip install pyserial

Verify Installation

Test that modules are installed correctly:

python -c "import cv2; print('OpenCV OK')"
python -c "import mediapipe; print('MediaPipe OK')"
python -c "import serial; print('PySerial OK')"

All three should print "OK" messages.

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Troubleshooting

Arduino Issues

• Upload fails: Check COM port is correct (Tools → Port)
• No serial connection: Reinstall Arduino USB drivers
• LEDs don't light up: Check pin connections and power supply

Python Issues

• "ModuleNotFoundError": Run pip install commands again
• Webcam not working: Check webcam is not in use by another program
• Serial port busy: Close Arduino IDE or other serial apps
• Change COM port: Edit main.py line 9: serial.Serial(port='COM4', ...) to your port

Hand Detection Issues

• Hand not detected: Ensure good lighting and clear hand visibility
• Fingers not detected: Make sure hand is fully in frame with fingers extended

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Project File Structure

MS101/
├── Arduino.cpp           # Arduino microcontroller code
├── main.py              # Python hand detection & control script
├── README.md            # This file
├── pic1.png             # Project photo 1
├── pic2.png             # Project photo 2
└── pic3.png             # Project photo 3

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How It Works

1. Python Side (main.py):

   • Captures video from webcam
   • MediaPipe analyzes hand landmarks
   • Detects which fingers are extended
   • Sends finger states to Arduino via serial port (9600 baud)

2. Arduino Side (Arduino.cpp):

   • Receives 5 bytes representing finger states (0 or 1)
   • Counts how many fingers are detected
   • Controls LEDs inversely (5 fingers → LED pin 8, 1 finger → LED pin 12)
   • Triggers buzzer on hand detection or when no fingers are found

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Connection Diagram

Laptop (Python)
    ↓ USB Cable
Arduino Uno
    ├── Pin 8 → LED 1
    ├── Pin 9 → LED 2
    ├── Pin 10 → LED 3
    ├── Pin 11 → LED 4
    ├── Pin 12 → LED 5
    ├── Pin 6 → Buzzer
    └── GND → Ground connection

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Notes

• The project uses inverse LED mapping (5 fingers lights LED at pin 8, 1 finger lights LED at pin 12)
• Buzzer plays two 1200Hz beeps when hand is first detected
• Serial communication runs at 9600 baud rate
• Ensure Arduino and Python are synchronized on the same COM port

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Author

Sam Nahutdo
MS101 Project - Hand Gesture Recognition Traffic Control System

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License

This project is for educational purposes.

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