Raspberry Pi-based Facial Recognition for Vehicle Access Control

The integration of advanced biometric security systems in modern vehicles has become crucial to enhance safety and user convenience. This paper presents the design and implementation of a Raspberry Pi-based facial recognition system for vehicle access control, utilizing the power of computer vision and machine learning to provide secure, keyless vehicle entry. The system employs a Raspberry Pi microcontroller, coupled with a camera module, to capture and analyze the driver’s facial features. OpenCV, a widely-used computer vision library, is integrated with a pre-trained deep learning model to perform facial detection and recognition in real-time. The system compares the captured facial data with pre-registered user profiles stored in a secure database. Upon a successful match, the Raspberry Pi sends a signal to unlock the vehicle, ensuring seamless and secure access. The necessity of adopting facial recognition technology for vehicle access lies in its non-invasive, hands-free nature, providing a more convenient and secure alternative to traditional key-based systems. Moreover, it adds an additional layer of security, minimizing the risk of unauthorized access through stolen keys or fob duplication. Experimental results demonstrate that the facial recognition system achieves a high accuracy rate of 95% under various lighting conditions and user angles. The average processing time for facial recognition is less than 1 second, ensuring swift vehicle access. Additionally, the system exhibits robust performance even with multiple registered users, confirming its scalability and practicality for real-world applications. This research highlights the potential of Raspberry Pi as a cost-effective, efficient platform for implementing facial recognition systems in vehicles, paving the way for further innovations in automotive security.