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🔹 Overview

A microcontroller-based system for accident detection, location tracking, and automatic emergency alerts. The device identifies collisions, rollovers, and fires, determines driver-carelessness level, and sends real-time GPS coordinates to emergency services via GSM.

See the demo video below for a quick visual explanation of how the system works.

Full system description referenced from project documentation.

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🔹 Features

• Accident Detection: Collision, rollover, and fire sensing
• Driver Carelessness Assessment: Based on activation order
• GPS Tracking: Real-time location via NEO-6M
• GSM Alerts: SMS sent to emergency units with:
  • Accident type
  • Google Maps link
  • Driver-carelessness note
• Cancel Switch: 5–15 second safety window
• LCD Display: Status, alerts, and countdown
• Kalman Filtering: IMU smoothing for accurate rollover detection

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🔹 Hardware Components

• Arduino Nano (ATmega328P)
• MPU6050 IMU (Accelerometer + Gyroscope)
• Vibration/Knock Sensor
• Flame Sensor
• NEO-6M GPS Module
• SIM800C GSM Module
• LM2596 Buck Converter
• 16×2 LCD (I2C)
• Buzzer, LEDs, Push Button

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🔹 Architecture

Architecture Summary

1. Detect accident via IMU, knock, and flame sensors
2. Identify accident type
3. Fetch location from GPS
4. Countdown (5–15s) displayed on LCD
5. User may cancel non-critical alerts
6. GSM sends emergency SMS with:
   • Accident category
   • Carelessness remark
   • GPS Google Maps link
7. Audible/visual alerts through buzzer + LEDs

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🧩 Accident Severity & Delay Logic

Collision	Rollover	Fire	Delay
Yes	No	No	15s
No	Yes	No	15s
Yes	No	Yes	10s
No	Yes	Yes	10s
Yes	Yes	No	5s
Yes	Yes	Yes	5s

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🔹 Results Summary

• Accident detection accuracy: 100%
• GPS tracking accuracy: 87%
• SMS delivery success: 93%
• Tested across multiple real-world road conditions

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📁 Suggested Project Structure

▶️ Getting Started

### 1️⃣ Upload Code
Open `accident_alert_system.ino` using Arduino IDE and install required libraries.

### 2️⃣ Assemble Hardware
Follow the wiring diagram for all sensor and module connections.

### 3️⃣ Power the System
Regulated 5V supply using LM2596 converter.

### 4️⃣ Test Scenarios
Simulate:
- Collision (knock)
- Rollover (IMU orientation)
- Fire (flame sensor)

Confirm countdown + SMS behavior.

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🔹 Sensor Filtering (IMU)

A Kalman filter was used to reduce noise in:

- Roll  
- Pitch  
- Yaw  

This provides more accurate rollover detection.

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🚧 Known Limitations

• Initial GPS fix may take 2–3 minutes
• GSM reliability varies by signal strength
• IMU drift under long operation
• Requires mobile network coverage

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🔹 Future Improvements

• Add camera module for visual confirmation
• Integrate heart-rate, alcohol, or drowsiness sensors
• Cloud-connected IoT dashboard
• AI/ML accident severity classification
• Vehicle-to-Cloud (V2C) link for smart mobility

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🔹 License & Citation

Apache License  
Version 2.0, January 2004  
http://www.apache.org/licenses/

• If you use this work in any form—academic, research, educational, or practical—please cite it as:

Kasthuriarachchi, S.D., 2023. Automatic Vehicle Accident Alert System. [Online] Available at: https://github.com/sadeep654/Automatic-Vehicle-Accident-Alert-System (Accessed: date-you-accessed).

• copyright

Copyright all rights reserved

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📩 Contact

Feel free to explore, fork, or reach out for collaboration or opportunities.