“Biometric Based Voting System”
Mrs. Radhika
Dept. Of ECE
Acharya Institute of Technology
Bengaluru, India
radhika_1144@acharya.ac.iin
Abhishek
Dept. Of ECE
Acharya Institute of Technology
Bengaluru, India
abhishekpatil2254@gmail.com
Darshan gouda S Patil
Dept of ECE
Acharya Institute of Technology
Bengaluru, India
darshangouda742@gmail.com
Deepak S P
Dept of ECE
Acharya Institute of Technology
Bengaluru, India
potadardeepak20@gmail.com
K Hari Srinivasa Reddy
Dept. Of ECE
Acharya Institute of
Technology
Bengaluru, India
harisrinivasareddy3@gmail.com
Abstract—The design is meant to increase the safety, clarity, and efficiency within the election process because of the incorporation of modern biometric and computer technologies. In the process of designing this BBVM, a Raspberry Pi 3 is used, which works as the processor; therefore, this asserts a mini, cost-effective platform for handling a voting system. An R307 Optical fingerprint sensor is used for authenticating individuals, ensuring that the identity of all voters is confirmed biometrically, without having the chance for multiple votes to occur fraudulently. An HD Logitech C270 Webcam helps in identifying individuals with visual assistance, who works as a secondary component that records the authentication and actual identity records. The BBVM has a digital display interface, which helps in giving easy-to-read commands to users, making it easy for the voters to use the system. The system uses a 16 GB storage card for storing the records of voters, images, and voting, while a stable power source, which is 5V, provides strong power to operate the systems. The use of male-female jumper wires helps in connecting components in a modular way, facilitating easy modification. The BBVM is a reliable, easy-to-use, and secured voting system used in small, normalized institutions for conducting elections, which can also serve as a prototype for developing a BBVM on a full large scale, with the aim of presenting a modern, secured, and robust computerized voting alternative for casting votes. Keywords— Biometric voting machine, Raspberry Pi 3, Optical fingerprint sensor R307, Face recognition, Real-time authentication, Anti-fraud voting system.
