Smart Bank Locker Access System Using AI-IoT With ESP32 CAM Enabled Multi Factor AuthenticationID: 2663 Abstract :The Increasing Need For Advanced Security Systems In Banking And High-value Asset Protection Has Intensified Due To Rising Cyber-physical Threats, With Global Financial Fraud Losses Exceeding 40 Billion USD Annually And Smart Security Systems Projected To Grow At Over 16% Per Year. Additionally, Traditional Locker Systems Remain Vulnerable To Unauthorized Access, Identity Spoofing, And Delayed Threat Detection, Necessitating Intelligent And Predictive Security Solutions. Conventional Locker Systems Rely On Single-layer Authentication Methods Such As Keys Or PINs, Which Are Prone To Theft, Duplication, Or Brute-force Attacks, And Lack Real-time Monitoring And Anomaly Detection Capabilities. Furthermore, They Do Not Provide Immediate Alerts Or Predictive Insights, Making Them Inefficient Against Modern Security Threats. To Overcome These Limitations, The Proposed AI-IoT Secure Smart Bank Locker Access System Utilizes The ESP32 Microcontroller To Implement A Predictive, Multi-layered Security Framework. The System Integrates Fingerprint Biometric Authentication, Keypad-based PIN Verification, And ESP32- CAM Facial Recognition To Establish A Robust Three-factor Authentication Mechanism. Upon Successful Validation, A DC Motorized Lock Grants Access, While LCD And Buzzer Modules Provide Real-time Feedback. The AI-driven Fraud Detection Module Continuously Analyzes Access Patterns To Identify Anomalies Such As Unusual Timings Or Repeated Failures, Triggering Preventive Actions Including System Lockdown And Instant Alerts. IoT Connectivity Enables Remote Monitoring, Real-time Notifications, And Data Logging For Enhanced Security Management. This Intelligent System Significantly Enhances Safety, Prevents Unauthorized Access, And Delivers A Scalable, Proactive Solution For Modern Secure Storage Applications. |
Published:14-4-2026 Issue:Vol. 26 No. 4 (2026) Page Nos:1688-1695 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to CitePabbala Priyanka1*, N. Saipavan2 , Ambati Nikitha2 , Lenkala Rakesh2 , Poola Madhav, Smart Bank Locker Access System Using AI-IoT with ESP32 CAM Enabled Multi Factor Authentication , 2026, International Journal of Engineering Sciences and Advanced Technology, 26(4), Page 1688-1695, ISSN No: 2250-3676. |