Iris Recognition Based Modern Voting System Using Deep Learning

This project introduces a Face and Iris Recognition-Based Voting System utilizing Convolutional Neural Networks (CNNs) to enhance voter authentication and prevent electoral fraud. The system captures a voter's face and iris via a webcam and verifies their identity using a CNN-trained model on registered voters’ biometric data. Additionally, fingerprint authentication adds another layer of security. After successful biometric verification, a One-Time Password (OTP) is sent to the voter's registered mobile number for final authentication before granting access to the voting interface. This multi-layered security approach ensures only legitimate voters can participate, mitigating risks like impersonation, multiple voting, and unauthorized access. A secure database stores voter details and ballots, ensuring data confidentiality and integrity. Designed with a user-friendly interface, the system improves accessibility while maintaining the privacy, security, and accuracy of the electoral process, making online elections more reliable and efficient.