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

Biometric options integrated with the surpassing conventional locks for the expedient advancement of smart home technology has revolutionized home security. The Hybrid Unified Multimodal Biometric Integration Algorithm (HUMBIA), is proposed in this paper, with integrated modules like voice, facial, and fingerprint recognition to progress admittance control. The proposed HUMBIA algorithm reduces False Acceptance Rates (FAR) and False Rejection Rates (FRR) by incorporating robust refuge scheme with enhanced accurateness through the use of the ESP32 microcontroller and an amalgamation of biometric sense modality. The reliable performance in a variety of scenarios is analysed to ensure the scheme's dynamic adaptation by changing ecological environments. The evaluation with recent current techniques demonstrates the better precision and sensitivity of HUMBIA's authentication. Contemporary hardware integrated with AI driven processes is suggested in the proposed system for advanced security and user expediency. This research can mark a significant and trending progression in smart home-based security scheme.