Overview:

This project focuses on creating an IoT-based intelligent system that detects cracks or faults on railway tracks in real time. The aim is to prevent railway accidents by continuously monitoring the tracks using sensors and notifying the authorities immediately when any structural damage or crack is detected. The system is especially useful for monitoring long-distance, remote, or unmanned railway tracks, where manual inspections are costly and time-consuming.

Key Features:

• Real-Time Crack Detection
  Detects cracks in railway tracks using vibration, ultrasonic, or IR sensors mounted on a mobile unit or robot.

• GPS Location Tracking
  Pinpoints the exact location of the crack and sends coordinates via GPS.

• Instant Notifications
  Sends alerts to railway control centers via SMS, app notifications, or web dashboard.

• Buzzer/LED Alert System
  On detection, a local buzzer or LED activates to indicate damage.

• AI Model for Fault Classification (Optional)
  Uses a machine learning model trained to classify minor vs major cracks based on sensor readings.

• Dashboard with Historical Logs
  Stores past crack data for analysis and maintenance planning.

Technology Stack:

• IoT Hardware Components:

  • Sensors: Ultrasonic Sensor, IR Sensor, Vibration Sensor

  • Microcontroller: Arduino Uno or ESP32

  • GPS Module: NEO-6M

  • GSM Module (SIM800L or similar) or Wi-Fi (ESP8266) for sending alerts

• Backend:

  • PHP / Java / Node.js

  • REST API to receive and store crack detection logs

• Frontend:

  • HTML, CSS, Bootstrap, JavaScript for dashboard

  • Optional: Android app or PWA for live alerts

• Database:

  • MySQL or MongoDB to store sensor data, GPS logs, crack details