Smart Visitor Intelligent Management System using AI, Aadhaar Verification, Face Recognition and Trust Scoring

This research presented a Smart Visitor Intelligent Management System (SVIMS) that enhances visitor authentication, monitoring, and security using artificial intelligence and secure identity verification techniques. The proposed system integrates Aadhaar OTP verification [7], AI-based face recognition [4], [15], QR code-based visitor entry [5], and a Trust Score mechanism to provide an intelligent and efficient visitor management framework. The developed system successfully addresses the limitations of traditional visitor management methods, which mainly depend on manual records and basic digital registration [1], [2]. By incorporating automated verification and behavioral analysis, the system improves authentication accuracy, reduces unauthorized access, and enhances operational efficiency [6]. One of the major achievements of this work is the implementation of an AI-based Trust Score model that enables predictive security analysis by evaluating visitor verification history, behavioral consistency, and suspicious activity patterns. The system also provides real-time monitoring, digital record management, and scalable architecture for modern organizations. The proposed system has significant real-world impact in environments such as police stations, colleges, hospitals, corporate offices, and government organizations where secure visitor monitoring is essential. The integration of intelligent technologies improves security management, reduces administrative workload, and supports faster and more reliable visitor processing. Overall, the proposed SVIMS provides a modern, scalable, and intelligent solution for digital visitor management and contributes toward the advancement of AI-driven smart security systems [6], [21].   “The experimental results confirm that the proposed system outperforms traditional and existing digital systems by integrating AI-based intelligence, secure authentication, and behavioral analysis, making it a robust and scalable solution for modern visitor management.”

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