Smart Security Systems for Real-Time Human Identification Through GAIT Mechanism

Abstract: The rapid evolution of technological landscapes has necessitated more sophisticated security solutions, with gait analysis emerging as a promising biometric identification technique. This innovative approach leverages individuals' unique walking patterns as a distinctive personal identifier, utilizing advanced computational methods. By integrating Sequential modeling for temporal data processing and MediaPipe Pose for precise pose prediction, the proposed system demonstrates remarkable accuracy and robustness in individual recognition. The methodology capitalizes on the nuanced biomechanical characteristics of human locomotion, transforming walking patterns into a reliable biometric signature. Preliminary research indicates significant potential for future developments, with anticipated enhancements including hybrid biometric integration and multi-person detection capabilities. This approach represents a significant stride in non-invasive, behavioral biometric technologies, offering promising applications across security, surveillance, and personalized authentication domains.