TRIBHUVAN UNIVERSITY

INSTITUTE OF ENGINEERING
ADVANCED COLLEGE OF ENGINEERING AND MANAGEMENT
DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING
KALANKI, KATHMANDU

A Major Project Proposal Report On

“Multi-Factor Biometric Door Lock System Using Raspberry Pi”

[Project Code: Ex 654]

Submitted By:

Missan Ban ACE078BEI027

Nabin Singh ACE078BEI028
Ronash Lamichhane ACE078BEI037
Samir Ban ACE078BEI042

A Major Project Proposal report submitted to the Department of Electronics and Computer
Engineering in the partial fulfillment of the requirements for degree of Bachelor of
Engineering in Electronics, Communication and Information Engineering
Kathmandu, Nepal
June 8, 2025
 ACKNOWLEDGEMENT

We take this opportunity to express our deepest and sincere gratitude to our Project
Coordinator Er. Ramesh Sharma, Department of Electronics and Computer Engineering
for his insightful advice, motivating suggestions, invaluable guidance, help and support in
this project selection and also for his constant encouragement and advice throughout our
Bachelor’s program.

We express our deep gratitude to Er. Roshni Ghimire, Head of Department of Electronics
and Computer Engineering, Er. Raksha Dangol, Deputy Head, Department of Electronics
and Computer Engineering for their regular support, co-operation, and coordination.

The in-time facilities provided by the department throughout the Bachelors program are also
equally acknowledgeable.

We would like to convey our thanks to the teaching and non-teaching staff of the Department
of Electronics & Communication and Computer Engineering, ACEM for their invaluable
help and support throughout the period of Bachelor’s Degree. We are also grateful to all our
classmates for their help, encouragement and invaluable suggestions.

Finally, yet more importantly, we would like to express our deep appreciation to our
grandparents, parents, siblings for their perpetual support and encouragement throughout
the Bachelor’s Degree period.

Sincerely,

Missan Ban ACE078BEI027

Nabin Singh ACE078BEI028

Ronash Lamichhane ACE078BEI037

Samir Ban ACE078BEI042

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 TABLE OF CONTENTS

Title Page

ACKNOWLEDGEMENT .................................................................................................. I

TABLE OF CONTENTS ................................................................................................... II

LIST OF TABLES ............................................................................................................ IV

LIST OF FIGURES............................................................................................................ V

List of Abbreviations/Acronyms ..................................................................................... VI

CHAPTER 1

INTRODUCTION ............................................................................................................... 1

1.1 Background ................................................................................................................. 1

1.2 Motivation ................................................................................................................... 1

1.3 Statement of Problem .................................................................................................. 1

1.4 Project Objective ......................................................................................................... 2

1.5 Significance of Study .................................................................................................. 2

CHAPTER 2

LITERATURE REVIEW ................................................................................................... 3

CHAPTER 3

REQUIREMENT ANALYSIS ............................................................................................ 5

3.1 REQUIREMENTS ANALYSIS .................................................................................. 5

3.1.1 Hardware Requirements ....................................................................................... 5

3.1.2 Software Requirements ........................................................................................ 5

3.1.3 Functional Requirements...................................................................................... 5

3.1.4 Non- Functional Requirements ............................................................................ 7

3.2 Feasibility Study.......................................................................................................... 8

3.2.1 Technical Feasibility............................................................................................. 8

3.2.2 Economic Feasibility ............................................................................................ 8

II
 3.2.3 Operational Feasibility ......................................................................................... 9

3.2.4 Schedule Feasibility ............................................................................................. 9

CHAPTER 4

SYSTEM DESIGN AND ARCHITECTURE ................................................................. 10

4.1 Block Diagram .......................................................................................................... 10

4.2 Flowchart ................................................................................................................... 11

CHAPTER 5

METHODOLOGY ............................................................................................................ 12

5.1 Requirement Analysis and Planning ......................................................................... 12

5.2 Hardware Setup and Interfacing ................................................................................ 12

5.3 Software Development .............................................................................................. 12

5.4 Testing and Validation ............................................................................................... 13

5.5 Documentation and Evaluation ................................................................................. 13

5.6 Deployment ............................................................................................................... 13

CHAPTER 6

EXPECTED OUTPUT ..................................................................................................... 14

CHAPTER 7

TIME SCHEDULE ........................................................................................................... 15

CHAPTER 8

COST ESTIMATE ............................................................................................................ 16

REFERENCES .................................................................................................................. 17

III
 LIST OF TABLES

Title Page

Table 8.1 Cost Estimate .....................................................................................................16

IV
 LIST OF FIGURES

Title Page

Figure 4.1 Block Diagram ...............................................................................................................10

Figure 4.2 Flowchart ........................................................................................................................11
Figure 7.1 Time Schedule ................................................................................................................15

V
 List of Abbreviations/Acronyms

GPIO General Purpose Input/Output

GSM Global System for Mobile Communication

GUI Graphical user interface

IDE Integrated Development Environment

IoT Internet of Things

OTP One-Time Password

PIN Personal Identification Number

RFID Radio-Frequency Identification

UART Universal Asynchronous Receiver/Transmitter

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CHAPTER 1
INTRODUCTION

1.1 Background

In this modern era, security concern is growing along with technological advancement. The
normal door locking systems no longer provide proper protection/security. Traditional
locking system using keys are prone to theft, duplication. With the advancement of
technologies and rise of smart homes, IoT (Internet of Things) and embedded systems, there
is a global shift toward intelligent security mechanisms which offers improved
authentication, automation, and user convenience.

Biometric authentication, such as fingerprint and facial recognition has emerged as a reliable
and secure method for identity verification. These technologies rely on physiological or
behavioral traits that are unique to individuals, which makes it difficult to forge or duplicate.
Integrating such biometrics with traditional security systems creates a multi-factor
authentication model that significantly strengthens access control.

1.2 Motivation

Security breaches at homes, offices and data-sensitive zones are due to the result of weak
authentication mechanisms. Even sometimes biometric systems, used in isolation condition
have limitations. For example, a fingerprint system alone may fail due to dirty sensors, or a
facial recognition module might not perform well in low lighting. A multi-factor approach
addresses these weaknesses by using at least two forms of verification, thus enhancing
reliability and security. And Raspberry Pi which is a cost-effective but powerful
microcontroller with built-in Wi-Fi and GPIO capabilities, is an ideal platform for such
embedded security systems. This project aims to utilize Raspberry Pi’s computational
capabilities to integrate multiple biometric authentication techniques as well as numeric
passcode with a user-friendly interface.

1.3 Statement of Problem

Most of the existing door locking systems depend on single-factor authentication like keys
or PINs, which can be easily compromised. Even single-mode biometric systems which is
more secure compared to traditional system possesses risks if used alone. The challenge is

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to develop a reliable, multi-modal authentication system which is both secure and
accessible. There is a requirement for a compact, low-cost and efficient solution that
combines multiple forms of authentication like fingerprint, face and passcode entry and can
be used in real-life applications.

1.4 Project Objective

• To develop a multi-factor biometric authentication system using Raspberry Pi.

1.5 Significance of Study

This project contributes significantly to the field of intelligent security systems. It provides
an affordable, easy to implement alternative compared to expensive commercial biometric
locks. It is modular in design, so it can be customized or scaled for use in homes, office
premises, laboratories, server rooms, and financial institutions. Additionally, this system
supports in digital record-keeping of user authentication attempts by providing an audit trail
for security purposes in case of requirements.

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CHAPTER 2
LITERATURE REVIEW

In the field of smart security systems, several studies and projects have explored biometric
authentication methods.
S. Alsaadi et al. (IEEE, 2020) proposed a layered authentication system combining
fingerprint recognition, RFID card scanning, and One-Time Password (OTP) verification
via GSM. This system effectively strengthened access control by requiring users to pass
through multiple authentication stages. The authors emphasized the importance of
combining hardware-based and network-based authentication for enhanced security.
However, the system lacked facial recognition and a graphical user interface, and it was
based on Arduino, which has limited processing power. This highlights the potential
advantage of using a Raspberry Pi, as proposed in this project, to incorporate more advanced
biometric processing and user interaction.[1]

A. Sharma et al. (IJERT, 2021) developed a facial recognition-based door lock using
Raspberry Pi, OpenCV, and a Pi Camera. The system used Haar Cascade classifiers for face
detection and successfully recognized authorized users under good lighting conditions.
However, the system struggled with performance in low-light or obstructed scenarios and
relied solely on face recognition, making it vulnerable to spoofing or recognition failures.
This research demonstrates the feasibility of deploying facial recognition on Raspberry Pi
but also underscores the importance of using multi-factor authentication, which is addressed
in the present project by combining facial recognition with fingerprint and keypad
verification.[2]

P. Mehta and R. Sinha (IJERT, 2019) developed an internet-connected door lock system
using RFID authentication and a mobile app interface. Their system was designed to log
entry data in Firebase and allowed remote control via smartphones. The integration of cloud-
based monitoring and control was a strong point, particularly for remote access scenarios.
However, the reliance on RFID as a single authentication factor made it less secure
compared to biometric methods. Your project advances beyond this by implementing local
biometric verification (fingerprint and face) and avoids dependence on network connectivity
for basic authentication.[3]

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V. Kulkarni and M. Patil (IJARCSSE, 2020) developed a system in which they implemented
fingerprint-based access control using the R305 fingerprint sensor interfaced with a
Raspberry Pi. It allowed basic user enrollment and verification through a Python script and
provided a simple GUI for interaction. While the system demonstrated accurate fingerprint
recognition and practical implementation, it lacked a secondary authentication mechanism
and didn’t include real-time visual feedback or surveillance features. The proposed project
builds on this foundation by integrating facial recognition and a PIN keypad, thereby
providing a robust, multi-layered authentication system suitable for high-security
applications.[4]

R. Singh and A. Verma (IJCA, 2020) proposed a door security system combining RFID,
fingerprint, and keypad authentication. The system was built on an Arduino Uno and used
an LCD display for user interaction. Their goal was to provide a cost-effective, layered
security mechanism. While the use of three different authentication methods added
robustness, the system had limitations in terms of processing capability and lacked a camera
module, making it unsuitable for facial recognition or image processing. Additionally, no
data logging or real-time monitoring features were implemented.[5]

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CHAPTER 3
REQUIREMENT ANALYSIS

3.1 REQUIREMENTS ANALYSIS

Our system has the following requirements:

3.1.1 Hardware Requirements

• Raspberry Pi 5
• Pi Camera Module
• R305 Fingerprint Sensor
• Reed Switch
• 7" Touch Display
• Relay Module
• Solenoid Lock
• Power Supply

3.1.2 Software Requirements

• Operating System: Windows
• Programming language: Python
• IDE- VS Code

3.1.3 Functional Requirements

1. User Authentication via Fingerprint
• The system must capture and process a user's fingerprint using a fingerprint sensor
(e.g., R305).
• It must match the fingerprint as per the stored template in the local database.
• If the fingerprint matches the registered user, the system will grant access (on the
basis of configuration).
• The system must support enrolling new fingerprints and deleting existing ones
(admin-only functionality).

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2. Facial Recognition Authentication
• The Raspberry Pi camera module should capture real-time facial images of the user
attempting for the access.
• Facial recognition should be performed using libraries such as OpenCV or face
recognition.
• The system should compare the live image taken during authentication with stored
facial data to verify the user's identity.
• If the face is recognized, it must grant access.

3. Keypad-Based PIN Entry

• A touchscreen keypad should allow users to enter a personal PIN code as part of the
authentication process.
• The system should verify the entered PIN against the stored records for the matched
user.
• While the PIN is correct, the system proceeds to unlock the door or grant access to
the user.
• The system should lock out the user or trigger an alert signal after continuous
multiple incorrect attempts.

4. Access Control Logic

• The system should use various logic for fingerprint, facial recognition, and PIN
verification.
• Access should only be granted when one out of three authentication methods are
successful.
• The system must control an electric locking mechanism to unlock or lock the door
accordingly.

5. Real-Time Display Interface

• A touchscreen connected to the Raspberry Pi must display system status (e.g.,
"Scanning Fingerprint", "Face Not Detected", "Access Granted/Denied").
• The interface should also allow administrators to enroll users, delete data, and view
authentication logs.

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 6. Logging and Alert System
• The system should log all access attempts (successful and failed) with timestamps
and authentication results.
• The system can send alerts (e.g., via email or SMS) when repeated unauthorized
access attempts are detected (Optional).

7. Power and Boot Management

• Upon system startup, it must initialize all modules (fingerprint sensor, camera,
display) and enter standby mode.
• In case of a power failure, the system must reboot automatically and restore
last known configurations.

3.1.4 Non- Functional Requirements

The non-functional requirement is a requirement that specifies criteria that can be used to
judge the operation of a system, rather than specific behaviors. Our system requires the
following non-functional requirements.

1. Performance:
• The system should respond to user input (fingerprint scan, face detection, PIN
entry) quickly i.e. within 2–3 seconds.
• Biometric recognition processes must maintain a high accuracy rate (≥95%) in
order to minimize false acceptances/rejections.
• The door locking mechanism should be activated within 1 second of successful
authentication.

2. Reliability:
• The system must be operational at least 99% of the time, with minimal
disturbances.
• All modules (camera, fingerprint, display) should function correctly while
using continuously.

3. Security:
• Biometric data and PINs must be stored securely in encrypted form.
• The system must lock out users or trigger an alert after certain number of
continuous failed authentication attempts.

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 • Only authorized users should have access to administrative functions.

4. Usability:
• The interface should be user-friendly with clear instructions and feedback.
• The system should be able to allow easy user enrollment, modification and
removal (controlled by admin).

5. Scalability:
• The system should support adding more users (e.g., up to 20) without
degradation in system performance.
• It should be modular and allow additional features which can be added later in
the system.

6. Maintainability:
• The codebase and hardware should be documented properly for easy updates
and troubleshooting.
• Logs should help to track issues and identify malfunctions.

3.2 Feasibility Study

A feasibility study is a detailed analysis that considers all of the critical aspects of a proposed
project in order to determine the likelihood of its succeeding.

3.2.1 Technical Feasibility

The project is technically feasible by using available components such as Raspberry Pi,
fingerprint sensor, camera module and touchscreen display. Open-source libraries like
OpenCV and Python’s face recognition module provide sufficient support for facial
recognition, whereas serial communication can be used to interface with the fingerprint
sensor. Raspberry Pi has the processing power and GPIO flexibility to handle multiple
peripherals and real-time responses which makes it a suitable platform for multi-modal
biometric authentication.

3.2.2 Economic Feasibility

The entire system is cost-effective with a total estimated budget within the limits for student
project. Most components are inexpensive and easily available and no any exclusive
software is required. The use of open-source software eliminates licensing costs. Moreover,

8
since the project does not rely on a constant internet connection or cloud services, ongoing
costs are minimal which makes it sustainable and budget-friendly.

3.2.3 Operational Feasibility

The system is designed to improve security through enhanced authentication methods and
its practical use in homes, offices, labs or banks makes it highly relevant to use. The user
interface will be simple and intuitive which allows both regular users and administrators to
interact with ease. Administrators can enroll and manage users with minimal training. The
project meets its intended purpose and provides real-world value and makes it operationally
feasible.

3.2.4 Schedule Feasibility

The development timeline is reasonable and is achievable within a final year academic
schedule. Hardware interfacing, software development, testing and integration can be
planned and executed within defined time period. Availability of different libraries,
development tools and extensive community support for Raspberry Pi and Python helps to
ensures that the delays caused due to technical challenges can be reduced.

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CHAPTER 4
SYSTEM DESIGN AND ARCHITECTURE

4.1 Block Diagram

Figure 4.1 Block Diagram

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4.2 Flowchart

Figure 4.2 Flowchart

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CHAPTER 5
METHODOLOGY

5.1 Requirement Analysis and Planning

• Identifying the hardware components like Raspberry Pi (Model 4 or 5), R305
fingerprint sensor, Pi Camera, display (e.g., 7" touchscreen), solenoid lock.
• Determining software libraries and frameworks as OpenCV, face recognition (for
face detection), Python serial communication for fingerprint module, and GPIO
handling for lock control.
• Define the authentication flow and logic as, at least one of three factors (face,
fingerprint, PIN) must match to grant access.

5.2 Hardware Setup and Interfacing

• Connect the fingerprint sensor to the Raspberry Pi via UART (TX/RX) GPIO pins.
• Connect the Pi Camera through the CSI port and enable it in the Pi configuration.
• Install and configure the touchscreen display for GUI output.
• Connect a solenoid lock module to control the physical locking mechanism.

5.3 Software Development

• Fingerprint Module: Use Python with the pyserial library to interact with the
fingerprint sensor and implement functionality to enroll, delete, and verify
fingerprints and store fingerprint IDs locally.
• Face Recognition Module: Use OpenCV and the face recognition library in order
to capture a real-time image and compare it with pre-stored encodings of registered
faces.
• PIN Module: Establish the pin entry mechanism within touchscreen and verify
entered PINs against a predefined list stored in a secure local database or config file.
• Access Logic Controller: Develop a Python script which combines input from all
three modules. Grant access if any one of the factors is successfully verified.
• GUI Interface: Develop a simple touchscreen interface with the help of Python to
display real-time status ("Face Detected", "Access Denied", etc.) and allow admin
functions like enrollment.

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5.4 Testing and Validation
• Unit Testing: Test each of the modules independently to ensure it performs properly
(e.g., test fingerprint recognition under various conditions).
• Integration Testing: Test the system end-to-end by performing full authentication
cycles with different combinations of valid and invalid conditions.
• Stress Testing: Perform repeated scans to check for false positives/negatives, time
delays and system stability.
• Failure Case Handling: Simulate incorrect inputs and system reboots to ensure
whether lockout and recovery mechanisms work as intended or not.

5.5 Documentation and Evaluation

• Maintain detailed documentation of system architecture, wiring diagrams and code
structure.
• Evaluate system accuracy (recognition rate), speed (response time) and user
experience.
• Collect feedback from different test users to improve usability and functionality.

5.6 Deployment
• Mount the system on a test door or a demo frame.
• Ensure all hardware is securely fixed and protected from physical tampering.
• Demonstrate final working model to evaluators, showcasing multi-factor
verification, user management and locking action.

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CHAPTER 6
EXPECTED OUTPUT

6.1 Multi-Factor Authentication System

A fully functional security system which authenticates users using three independent factors:
fingerprint recognition, facial recognition and PIN. The system should verify at least one of
these methods before granting access.

6.2 Real-Time Access Control

The door should unlock automatically within a few seconds upon successful authentication
and relock after a defined interval of time or when the door is closed.

6.3 User-Friendly Interface

A touchscreen-based GUI will guide the user through each steps scanning, PIN entry, result
notification and allows admin access for enrolling or deleting users.

6.4 High Security and Low False Rates

The system should achieve high accuracy with minimal false acceptance or rejection, even
under varying lighting and environmental conditions.

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CHAPTER 7
TIME SCHEDULE

Gantt Chart
0 20 40 60 80 100 120 140 160 180 200

Documentation and Finalization

Validation and Testing

Prototyping and Development

Defining Components and its source

Detail Design

Literature Review

Visualization and Rough Modelling

Project Planning

Duration (Days)

Figure 7.1 Time Schedule

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CHAPTER 8
COST ESTIMATE

Item Cost (NPR)

Raspberry Pi 5 22,500
R305 Fingerprint Sensor 4,000
Pi Camera Module 2,000
Reed Switch 150
7-inch Touch Display 8,500
Solenoid Lock 1,200
Relay Module 200
Miscellaneous (wires, casing, power supply) 4,500

Total 44,050

Table 8.1 Cost Estimate

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REFERENCES

[1] Alsaadi, S., Al-Azawi, M., Al-Dhaheri, H., & Alhammadi, M. (2020). A Multi-Layered
Authentication Access System Using Fingerprint, RFID, and OTP via GSM. In
Proceedings of the IEEE International Conference on Computer and Communication
Engineering (ICCCE), pp. 300–305. IEEE.

[2] Sharma, A., Yadav, R., & Goyal, M. (2021). Face Recognition-Based Door Lock System
Using Raspberry Pi and OpenCV. International Journal of Engineering Research &
Technology (IJERT), 10(6), 1–4.

[3] Mehta, P., & Sinha, R. (2019). IoT-Based Smart Door Locking System Using RFID and
Firebase. International Journal of Engineering Research & Technology (IJERT), 8(12),
25–28.

[4] Kulkarni, V., & Patil, M. (2020). Fingerprint-Based Door Locking System Using
Raspberry Pi. International Journal of Advanced Research in Computer Science and
Software Engineering (IJARCSSE), 10(5), 18–22.

[5] Singh, R., & Verma, A. (2020). Smart Door Lock System Using Multi-Factor
Authentication. International Journal of Computer Applications (IJCA), 176(28), 12–15.

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