Bank Locker Security System Using Machine Learning

Samiksha Wagaj, Vaishnavi Gund, Sonali Mane, Divya Sapkal and I.Y.Inamdar
Additional contact information
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

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 6, 246-251

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.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.14Issue6/246-251.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-14-issue-6/246-251.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:14:y:2025:i:6:p:246-251

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().