International Science Community Association Research Journal of Engineering Sciences 15 2 2026 05 26 Design and Development of a Secure door access module using Finger print, Face and Pin authentication 6 10 EN Alimova Zebo 1 Candidate of Technical Sciences, Professor, Department of Transport Energy Devices, Tashkent State Transport University, Tashkent, Uzbekistan Qurbonov Akrom 2 Tashkent State Transport University, Tashkent, Uzbekistan P.O. Isi 1 Department of Physics and Industrial Physics, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria Ofuaro 2 Department of Electronics and Computer Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria S. 3 Department of Electronics and Computer Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria Chinedu 4 Department of Physics and Industrial Physics, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria B.C. 5 Department of Physics and Industrial Physics, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria Ikenga 6 Department of Physics and Industrial Physics, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria O.A. 7 Department of Physics and Industrial Physics, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria Muomeliri 8 Department of Physics and Industrial Physics, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria C.B. 9 Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria (TET Fund Centre of Excellence in Biomedicine, Engineering and Agricultural Translation Studies) Orizu 10 Department of Physics, University of Abuja, Nigeria G.E. 11 Ndukwe 12 F.O 13 Alor 14 K.P. 15 Aribodor 16 D.N. 17 Isah 18 J. 19 > Research Paper 2026 4 14 2026 05 26 This paper presents the design and development of a secure door access module that integrates fingerprint recognition, facial authentication, and PIN verification into a single multi-factor security system. The system addresses the growing need for robust, user-friendly, and reliable access control in smart buildings, restricted facilities, and Internet of Things (IoT) ecosystems. The hardware architecture comprises an Arduino Mega microcontroller, a high-resolution capacitive fingerprint sensor (R305), a Raspberry Pi Camera Module V2 for facial recognition, a 4×4 matrix keypad for PIN entry, a magnetic door lock, a relay module, an LCD display, and a buzzer for audio-visual feedback. The software framework leverages OpenCV and Dlib libraries for face detection and recognition, while fingerprint matching is achieved through minutiae-based algorithms. The system operates in three independent authentication modes, each granting access upon successful verification. Experimental results show that the system achieves a false acceptance rate (FAR) of 0.01% and a false rejection rate (FRR) of 0.1% under controlled conditions. The system also incorporates a privacy-preserving biometric template protection scheme and an adaptive access control model that temporarily locks out users after three consecutive failed attempts. The proposed solution demonstrates strong resilience against common attack vectors such as spoofing and key duplication. This work contributes a practical, low-cost, and scalable biometric access control solution suitable for residential, institutional, and commercial applications. Copyright@ International Science Community Association