Digital Voting System with Face Recognition

The conduct of elections in many organizations and institutions continues to depend on traditional or semi-digital voting mechanisms, which are prone to impersonation, duplicate voting, operational delays, and human error. Critical processes such as voter authentication, vote casting, and result compilation often lack adequate security and transparency. Existing digital voting solutions provide partial automation but fail to ensure robust identity verification and secure handling of sensitive electoral data. This study presents the Digital Voting System with Face Recognition, an automated and secure platform designed to enhance the voting process through biometric-based voter authentication. The system employs face recognition techniques to verify voter identity before allowing vote casting, thereby ensuring the principle of “one person, one vote.” Automated vote recording and result generation improve efficiency, accuracy, and transparency. Experimental evaluation demonstrates reduced voting fraud, faster processing, and increased reliability compared to conventional methods. Future enhancements include integration with national identity databases, blockchain-based vote storage, mobile application support, and cloud deployment to enable large-scale, secure, and scalable election management.