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Bank Locker Security System Using Machine Learning

Author

Listed:
  • Samiksha Wagaj

    (SMSMPITR Institute of Technology, Akluj, India)

  • Vaishnavi Gund

    (SMSMPITR Institute of Technology, Akluj, India)

  • Sonali Mane

    (SMSMPITR Institute of Technology, Akluj, India)

  • Divya Sapkal

    (SMSMPITR Institute of Technology, Akluj, India)

  • I.Y.Inamdar

    (SMSMPITR Institute of Technology, Akluj, India)

Abstract

This project presents a highly secure and intelligent Bank Locker Security System that integrates multiple layers of authentication, including face recognition, OTP verification, and traditional physical key access, to ensure maximum safety and reliability. The system aims to overcome the limitations of conventional bank locker mechanisms by introducing a multi-factor authentication model that minimizes the risk of unauthorized access and theft. The face recognition module, powered by AI, authenticates the customer using live camera input, while a one-time password (OTP) sent to the registered mobile number acts as a second layer of security. Only after successful verification of both digital steps is the customer allowed to use the physical key to access the locker, thereby creating a robust three-level authentication system. The solution also includes an admin dashboard for locker management, user access control, and real-time security logs. This modernized locker system enhances trust, improves security standards, and brings smart automation to traditional banking services.

Suggested Citation

  • Samiksha Wagaj & Vaishnavi Gund & Sonali Mane & Divya Sapkal & I.Y.Inamdar, 2025. "Bank Locker Security System Using Machine Learning," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 14(6), pages 246-251, June.
    • Handle: RePEc:bjb:journl:v:14:y:2025:i:6:p:246-251
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