Unified AI-Based Biometric Authentication: A Low-Power, High-Security Solution

The rapid advancement of smart home technology has revolutionized the way we approach residential security. As traditional locking mechanisms become increasingly vulnerable to sophisticated attacks, the need for innovative and robust security solutions has never been greater. This paper introduces an advanced intelligent door lock system designed to meet the increasing demands for secure and efficient access control. The system integrates cutting-edge hardware components such as the ESP32 microcontroller, OLED display, Wi-Fi module, and specialized recognition devices including a fingerprint scanner, facial recognition camera, and voice recognition module. These components work in synergy to offer robust biometric authentication capabilities, enhancing both security and user convenience. The system's software architecture utilizes optimized algorithms for each biometric modality, ensuring reliable performance under varying environmental conditions. Central to its operation is the Unified Multimodal Biometric Integration Algorithm (UMBIA), which combines fingerprint, facial, and voice recognition data into a unified feature vector. This algorithm employs machine learning classifiers to evaluate the fused features against stored templates, ensuring high accuracy and adaptability. The proposed system represents a significant advancement in access control technology, promising enhanced security and seamless integration with smart home ecosystems.