Laser Transceiver Morse Code System

A communication system using Arduino, laser modules, and photoresistors to send and decode Morse code messages via light signals. This project bridges old-school Morse code with modern embedded systems for wireless optical communication.

Overview

This project demonstrates how to transmit text using Morse code over a laser beam and decode it using an Arduino-based receiver. It's ideal for educational, hobbyist, and backup communication applications where low power and high security are priorities.

Features

• Arduino-based transmitter and receiver
• Real-time encoding/decoding of Morse code
• Adaptive light thresholding for noise resistance
• Interrupt-driven data capture for higher accuracy
• Visual debugging via serial monitor

System Architecture

1. Transmitter:

   • Arduino with a laser module
   • Encodes characters into Morse code
   • Blinks laser on/off to send dot/dash signals

2. Receiver:

   • Arduino with a photoresistor (LDR)
   • Decodes laser blinks into Morse symbols
   • Reconstructs readable characters using a binary tree

Hardware Required

• 2× Arduino Uno/Nano
• 1× KY-008 Laser Module
• 1× LDR (Photoresistor)
• 1× 1KΩ Resistor
• Breadboard, wires, USB cables

Software Components

• Encoder Sketch (encoder/encoder.ino): Converts string to Morse and flashes laser
• Decoder Sketch (decoder/decoder.ino): Detects light signals and decodes Morse
• Logic Processor: Adjusts for ambient light changes dynamically
• Interrupt Service Routine: Captures signal transitions with millisecond precision
• Morse Tree Decoder: Translates signals into characters using a binary tree

File Structure

Folder	Description
encoder/	Code for transmitting Morse code
decoder/	Code for receiving and decoding Morse
diagrams/	System flowcharts and hardware schematics
docs/	Research paper and documentation
images/	Prototype images and visuals

Performance

• 📡 Range: ~300 meters (line of sight)
• 💬 Speed: ~80 WPM (Words Per Minute)
• 🔐 Security: Laser beam minimizes signal leakage
• ⚡ Power: Ultra-low power usage

Use Cases

• Disaster response communications
• Learning Morse code with real hardware
• Low-cost remote sensing & signaling
• Hobbyist or student electronics projects

Limitations

• Performance depends on environmental light conditions
• Line-of-sight required for signal transmission
• Basic version lacks encryption or robust error correction

Future Improvements

• Range extension via beam focusing or relays
• Secure transmission using encryption
• Mobile app interface for control and display
• AI-based error correction and adaptive encoding

Documentation

Find the full research write-up in reaserch paper, including methodology, analysis, and references.

Authors

• Parth Pawar
• Manish

B.Tech CSE, MIT — Semester IV