MULTIMODAL MICROPROCESSOR DEVICE FOR HUMAN BIOMETRIC IDENTIFICATION

Abstract

This utility model relates to microprocessor technology, biometric identification systems, and embedded intelligent devices designed for automatic personal recognition based on multiple biometric characteristics. The proposed utility model is a multimodal microprocessor-based biometric identification device comprising a fingerprint scanner, a voice identification module, a microprocessor computing module, a memory module, a neural network data processing unit, a decision-making unit, a communication interface, and a power source. A distinctive feature of the utility model is its use of a unified microprocessor architecture, enabling local intelligent processing of multiple biometric modalities without the need to transmit data to external computing servers.The microprocessor computing module collects, digitally filters, extracts features, analyzes, and compares user biometric data with templates stored in the device's memory. Fingerprints and voice characteristics are used as biometric features. Combined processing of multiple biometric parameters improves identification accuracy, reduces the likelihood of false positives and false negatives, and enhances the system's resilience to external influences and noise. The technical result of this utility model is increased reliability, speed, and autonomy of biometric identification through the use of integrated microprocessor processing of multimodal biometric data and recognition algorithms.The utility model can be used in access control and management systems, banking and financial systems, mobile devices, medical information systems, critical infrastructure facilities, government personal identification systems, and intelligent IoT systems. The proposed device is compact, capable of autonomous operation, offers high data processing speeds, and can be integrated into modern digital security systems.

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