Abstract:
Electoral tampering, or voting irregularities, leads to an unlawful intervention in the electoral process, wherein voters successively cast ballots in favor of a particular party, thereby distorting the outcome. Ethical conduct of elections constitutes the legal practices of the electoral system. Consequently, an Artificial Intelligence-based electronic voting system has been considered to address this issue. Current systems, characterized by manual processes, are both time-consuming and hard to maintain. The proposed system integrates various biometric processes, including face detection, CNIC card reading through QR code, and fingerprint sensors, to enhance efficiency and accuracy. Noticeably, the system reduces human interference, employing automated mechanisms for voter authentication and ballot casting. A camera captures electors’ images, which are ultimately stored in a database for analysis. Data analysis includes training labeled images through a convolutional neural network to categorize and predict the results accurately.
