Smart Accident Detection & Voice-Based Emergency Response System
CrashGuard is a real-time accident detection system built on Raspberry Pi that combines motion sensing, GPS tracking, and voice interaction to reduce emergency response time after a crash. When abnormal motion is detected, the system engages the driver in a voice-based check-in and, based on their response (or lack thereof), automatically dispatches an emergency alert with location and incident details.
"Detect. Confirm. Respond."
- Overview
- Key Features
- Hardware Used
- Technologies Used
- How It Works
- Alert Contents
- System Architecture
- Getting Started
- Future Improvements
- Disclaimer
- License
CrashGuard continuously monitors vehicle movement using an accelerometer and gyroscope. Upon detecting abnormal motion consistent with a collision, it initiates a voice interaction to confirm the driver's condition, retrieves GPS coordinates, and — depending on the outcome — automatically sends an emergency alert to designated contacts.
| Feature | Description |
|---|---|
| 🚨 Real-Time Accident Detection | Continuous motion monitoring via accelerometer and gyroscope |
| 🎤 Voice-Based Driver Confirmation | Interactive check-in using speech recognition and TTS |
| 📍 GPS Location Tracking | Live location capture at the time of incident |
| 📧 Automatic Email Alerts | Sends incident report with location and severity |
| 🧠 Smart Decision Logic | Differentiates between confirmed-safe, confirmed-unsafe, and no-response scenarios |
| 📊 GUI Dashboard | Live monitoring interface built with Tkinter |
| 📝 Incident Logging | Persistent record of detected events and outcomes |
- Raspberry Pi — core processing unit
- MPU6050 — accelerometer + gyroscope for motion sensing
- Neo-6M GPS Module — location tracking
- WM8960 Audio HAT — microphone and speaker for voice interaction
- Python 3
- Raspberry Pi OS
- I2C & UART communication protocols
- Speech Recognition
- Text-to-Speech (TTS)
- Tkinter (GUI)
- Monitor — The system continuously tracks acceleration and tilt data from the MPU6050.
- Detect — If abnormal motion is identified, an accident is suspected.
- Confirm — The system verbally asks the driver: "Are you okay?"
- Analyze Response:
- ✅ "I am okay" → Alert is cancelled
- ❌ "Not okay" → Alert is sent
- ⏳ No response → Alert is sent automatically
- Locate — GPS coordinates are retrieved.
- Alert — An emergency email is dispatched with full incident details.
Each emergency alert includes:
- 📍 GPS coordinates with a Google Maps link
- ⏱️ Timestamp of the incident
⚠️ Severity level- 🧾 Full incident report
flowchart LR
A[Motion Sensors<br/>MPU6050] --> B[Detection Logic<br/>Python]
B --> C[Voice Interaction<br/>Mic / Speaker]
C --> D[Response Analysis<br/>OK / Not OK / No Response]
D --> E[Alert Dispatcher<br/>Email + GPS]
D --> F[Incident Log<br/>Local Storage]
E --> F
- Raspberry Pi (3B+ or newer recommended)
- Python 3.7+
- MPU6050, Neo-6M GPS module, and WM8960 Audio HAT wired per hardware documentation
- Internet connectivity (for email alerts)
# Clone the repository
git clone https://github.com/<your-username>/crashguard.git
cd crashguard
# Install dependencies
pip install -r requirements.txt
# Configure email credentials and thresholds
cp config.example.py config.py
nano config.pypython3 main.py- 📶 GSM module integration for SMS alerts
- 📱 Mobile app integration
- ☁️ Cloud-based incident logging
- 🤖 AI-based crash detection for improved accuracy
- 📷 Camera integration for visual incident confirmation
This is a prototype system designed for educational purposes. It may require further testing, calibration, and optimization before being considered for real-world deployment. It is not a certified safety device and should not be relied upon as a sole means of emergency response.
This project is licensed under the MIT License.
CrashGuard — Detect. Confirm. Respond.