UTILIZING MACHINE LEARNING TO FACILITATE ELECTRONIC VOTING THROUGH TWO STEP VERIFICATION

Author: D. Sudhandhira and Dr. V. Maniraj

Published On: 2025-03-10

India is the world's biggest democratic organization. So it is significant to ensure that the governing body is elected in a fair election. India only has an offline voting system, which is ineffective and inefficient because it requires a big number of people and takes longer to process and publish results. To be effective, the system requires a redesign that addresses these shortcomings. The new system does not require a person's physical appearance to vote, making the process easier. We used deep learning techniques for face recognition for voting system. This paper examines a system that enables users to vote remotely from any location using a computer or mobile device, eliminating the need for voters to visit polling stations using a two-step authentication process involving facial recognition and an OTP (one time password) system. We used C-NN (Convolution Neural Network), these are perfect for activities involving facial and picture recognition. This paper also allows users to vote offline if they prefer to do so. The system verifies the image by two-step verification. The face scanning system is used to capture voters' faces before the election and is handy during voting. RFID tags, rather than voter identification, are used to improve the offline voting system. This technology also allows citizens to see the results at any moment, preventing situations that possibly will lead to vote ropes.