Facial Recognition Authentication in Electoral Processes using Raspberry Pi

Elections serve as the basis of democratic governance by offering people the power to elect their Delegates. Upholding the integrity and trust worthiness of these election procedures is vital in preserving democratic values. This work is dedicated to reinforcing the trust through the implementation of progressive technology to safeguard the duplicity of the voting process. The initiative focuses on bolstering the security measures within electoral systems by harnessing advanced facial recognition technology. Leveraging Raspberry Pi a compact computing solution paired with cameras, the aim is to authenticate voters' identities accurately. To achieve this, we utilized the FaceNet model from DeepFace library, which in comparison with other models, was found to have a greater accuracy of 99.63%. Facial recognition integration is a proactive measure to deter fraudulent practices, particularly voter impersonation, during election processes. The primary objective is to establish an electoral system characterized by security and trustworthiness. Facial recognition technology in this context seeks to validate each vote's legitimacy and ensure it corresponds to the rightful voter. This approach aims to instill confidence in the electing process, providing a fair-minded and dependable system aligned with democratic principles of honesty and transparency.