FINGERPRINT BASED ELECTRONIC VOTING
MACHINE ACADEMIC YEAR: 2025-26
Abstract
This project presents a fingerprint-based electronic voting machine (EVM) aimed at
providing a secure, low-cost, and portable voting solution for small-scale elections. The
system integrates biometric authentication via a fingerprint sensor to ensure each voter can
vote only once, preventing impersonation and duplicate voting. Upon successful
authentication, the voter selects their preferred candidate via push-buttons or a touchscreen
interface. Votes are stored securely in an encrypted SD card, along with a timestamp and
tamper log, ensuring data integrity. An optional Wi-Fi module (ESP32) enables secure, real-
time transmission of results to a central server. The design is modular, scalable, and
adaptable, making it ideal for community elections, educational institutions, and research
demonstrations
Introduction
Free and fair elections form the foundation of any democratic society. The credibility of such
elections depends heavily on the accuracy of voter authentication and the prevention of
fraudulent activities. In small-scale elections, such as those held in educational institutions,
cooperative societies, or community organizations, the use of manual voting methods often
introduces risks such as duplicate voting, impersonation, and ballot manipulation. Traditional
paper ballots, while secure in principle, require significant manual handling and time for
counting, making them inefficient for quick and transparent results.
Biometric technology, especially fingerprint authentication, offers a reliable and cost-
effective way to verify voter identity. Unlike voter ID cards or PIN numbers, fingerprints are
unique to each individual and cannot be easily forged or shared. By integrating a fingerprint
sensor with a microcontroller-based voting system, it becomes possible to ensure that each
voter is authenticated once and only once. This drastically reduces the chances of duplicate
voting and strengthens the overall security of the election process.
The proposed system operates in two primary phases — authentication and voting. During
authentication, the fingerprint sensor scans the voter’s finger and compares it to a pre-
enrolled database. If the fingerprint matches, the voter is granted access to cast their vote via
push-buttons or a touchscreen interface. The selected vote is then securely stored in an
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FINGERPRINT BASED ELECTRONIC VOTING
MACHINE ACADEMIC YEAR: 2025-26
encrypted SD card along with a timestamp, while also maintaining a tamper-evident log to
ensure data integrity. Optional network connectivity via ESP32 can be used for secure, real-
time transmission of vote data to a central server.
The scope of this project extends beyond academic demonstration. Such a system can be
adapted for use in smaller-scale official elections where the deployment of certified large-
scale EVMs is impractical due to budget or logistical constraints. Furthermore, it serves as an
educational tool to understand the integration of biometrics, embedded systems, and data
security principles, offering practical exposure to students in electronics and computer
engineering fields.
Literature Review
1. Secure Biometric Voting Systems: Architectures and Challenges. Journal of
Electronic Voting.
R. K. Sharma, & L. Gupta (2022), 14(2), 45–62
Discusses design and architecture of biometric-enabled voting systems, highlighting the role
of unique physiological traits in preventing impersonation, while emphasizing encryption and
tamper-evidence to maintain trust
2. Design of Portable EVMs Using Microcontrollers and Biometric Sensors
T. Nguyen, et al. (2021), IEEE Access, 9, 11234–11246.
Presents a microcontroller-based portable voting machine with biometric authentication,
noting benefits like portability, low power consumption, and reduced operational costs for
small-scale elections.
3. Tamper-Evident Logging for Embedded Voting Machines. ACM Transactions on
Embedded Systems
S. Patel & A. Rao (2020). 19(3), 34–49.
Introduces methods for tamper-evident audit logs in embedded systems, inspiring secure
vote recording methods and detection of unauthorized access attempts
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FINGERPRINT BASED ELECTRONIC VOTING
MACHINE ACADEMIC YEAR: 2025-26
4. Comparative Study of Fingerprint Modules and Authentication Latencies.
M. Khan & P. Singh (2023). Sensors, 23(5), 987.
This study compares fingerprint sensors on accuracy, response time, and cost, guiding the
selection of suitable modules for real-time voting applications.
5. Secure Data Storage on Microcontrollers: Encryption & SD Card Best Practices
A. Ahmed et al. (2019). International Journal of Secure Systems, 6(1), 77–93.
This paper describes a cloud-based IoT healthcare system that allows healthcare
professionals to monitor patients remotely using a mobile app. It also discusses the use of
data analytics to predict health trends and detect anomalies based on historical data.
Objectives
• To design and implement a fingerprint-based authentication system for secure voting.
• To prevent multiple voting by the same individual through biometric verification.
• To store votes securely with encryption and timestamps for audit purposes.
• To integrate tamper detection and log security breaches.
• To create a portable, low-cost, and easy-to-use voting machine prototype.
Methodology
1. Voter Enrolment: Admin enrols fingerprints into the database via fingerprint module.
Assigns voter ID linked to the fingerprint template.
2. Authentication: Voter places finger on the sensor. If matched, voter proceeds to voting
stage; otherwise, access denied.
3. Voting: Candidate selection via buttons or touchscreen. Confirmation screen to prevent
accidental voting.
4. Vote Storage: Encrypt and store vote data (candidate ID, time, voter hash) in SD card.
Maintain append-only logs for integrity.
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FINGERPRINT BASED ELECTRONIC VOTING
MACHINE ACADEMIC YEAR: 2025-26
5. Tamper Detection & Alerts: Case-open switch logs tamper events. Alerts via
buzzer/display and optional network transmission.
6. Result Tally & Export: Admin-only access to tally votes. Option to export logs or upload
securely to central server.
Hardware Components
• Arduino Uno / Mega or ESP32 – The main microcontroller for processing and controlling
the system.
• Fingerprint Module (R305/ZFM-20) – For biometric authentication and secure
identification.
• 16×2 LCD with I²C or TFT Display – To display system information, status, and user
prompts.
• SD Card Module + Micro SD – For storing data logs and records.
• RTC Module (DS3231) – Real-Time Clock module for accurate timekeeping.
• Push-buttons / Keypad – For user input and navigation.
• Buzzer, LEDs – For audio-visual alerts and status indication.
• Li-ion Battery + TP4056 Charger – Rechargeable power source with charging module.
• Enclosure & Mounting Hardware – For housing and securing the components.
Software Components
• Arduino IDE – The primary software platform for programming and uploading code to the
microcontroller.
• Fingerprint Sensor Library – For interfacing and managing fingerprint module
operations.
• SD and RTC Libraries – To handle data storage and real-time clock functions.
• AES Encryption Library – For securing stored and transmitted data.
Conclusion
The fingerprint-based electronic voting machine offers a secure, efficient, and portable
solution for small-scale elections. By combining biometric authentication, encrypted vote
storage, and tamper detection, the system ensures high integrity and reliability. Its modular
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FINGERPRINT BASED ELECTRONIC VOTING
MACHINE ACADEMIC YEAR: 2025-26
design allows for upgrades such as wireless result transmission and larger-scale deployment,
making it a versatile prototype for both academic and real-world applications.
Expected Results
• High-accuracy authentication: The fingerprint sensor will correctly identify registered
voters with a response time of under two seconds, ensuring smooth voter flow.
• Prevention of vote duplication: Biometric verification will ensure that no voter can
cast more than one vote during the election period.
• Secure vote recording: All votes will be stored in encrypted form on the SD card,
along with timestamps and unique tamper flags for audit purposes.
• Tamper and fault alerts: The system will provide immediate visual and audible alerts
in the event of enclosure opening, low battery, or unauthorized access attempts.
• Stable operation: The device will operate reliably for the entire voting session on
battery power, with efficient power management to avoid downtime.
• Optional remote monitoring: The ESP32 module will enable secure, real-time
transmission of vote tallies to a centralized server for transparent result aggregation.
• User-friendly experience: Both voters and administrators will find the interface simple
to use, minimizing the need for technical training..
References
1. R. K. Sharma, & L. Gupta, “Secure Biometric Voting Systems: Architectures and
Challenges,” Journal of Electronic Voting, vol. 14, no. 2, pp. 45–62, 2022.
2. T. Nguyen, P. Tran, and L. Huynh, “Design of Portable EVMs Using Microcontrollers and
Biometric Sensors,” IEEE Access, vol. 9, pp. 11234–11246, 2021.
3. S. Patel, & A. Rao, “Tamper-Evident Logging for Embedded Voting Machines,” ACM
Transactions on Embedded Systems, vol. 19, no. 3, pp. 34–49, 2020.
4. M. Khan, & P. Singh, “Comparative Study of Fingerprint Modules and Authentication
Latencies,” Sensors, vol. 23, no. 5, article 987, 2023.
5. A. Ahmed, M. Zafar, & R. Hussain, “Secure Data Storage on Microcontrollers: Encryption
& SD Card Best Practices,” International Journal of Secure Systems, vol. 6, no. 1, pp. 77–
93, 2019.
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