Embedded Sentry System
Abstract
This project implements an innovative "Embedded Sentry" system using gesture recognition for secure access control. The system utilizes a single accelerometer/gyroscope to record and authenticate unique hand movement sequences, providing a novel biometric approach to protecting assets and sensitive data.
Technical Implementation
Hardware Components
- STM32F49I Discovery Board with integrated motion sensors
- Custom PCB for signal processing and power management
- LED indicators for system feedback
- Tactile push buttons for user interaction
Software Architecture
- PlatformIO development environment
- C++ firmware with real-time processing capabilities
- Custom gesture recognition algorithms
- Secure storage of gesture templates
Key Features
Gesture Authentication
Unique motion-based authentication system that records and verifies complex hand gestures with high accuracy
Secure Storage
Encrypted storage of gesture templates to prevent unauthorized access or duplication
Visual Feedback
Comprehensive LED status indicators for system state and authentication results
Compact embedded system with integrated motion sensing and user interface components
From motion capture to authentication decision - the complete processing pipeline
Comprehensive state machine handling all operational modes and transitions
Performance and Impact
Security
Biometric gesture recognition provides strong authentication resistant to common attacks
Performance
Real-time processing with response times under 500ms for typical gestures
Flexibility
Adaptable to various security scenarios through customizable gesture complexity
Future Enhancements
- Integration with wireless communication modules for remote access control
- Machine learning-based gesture recognition for improved accuracy
- Multi-factor authentication combining gestures with other biometrics
- Low-power modes for battery-operated deployments
Conclusion
The Embedded Sentry System demonstrates the viability of motion-based authentication in embedded environments. By combining robust hardware with sophisticated gesture recognition algorithms, this project provides a foundation for innovative security solutions that are both secure and intuitive to use. The system's performance and flexibility make it suitable for applications ranging from personal device security to industrial access control, with significant potential for future expansion and refinement.