Artificial Intelligence and Communication Technologies
College Election System using Facial Authentication
Authors: Akash Maurya, Pooja Shetty, Ganesh Yadava and Leena Ladge
Publishing Date: 08-10-2022
ISBN: 978-81-955020-5-9
Abstract
Voting is commonly related to politics and is often ended with exploitation. Manual voting may lead to malpractices sometimes, so there is a need to implement a secured online voting system. The voting system that we propose is a web portal which is designed using the MERN stack and the authentication of the voter is done using facial recognition. For this, the Eigen-face algorithm is used. The user will have to register and login into the portal. After that, the users will upload their respective documents which will be verified by the admin. For the voter’s assistance, the portal has several features like slot booking for the voting day, reminders for the voters, viewing of the candidates standing for the elections and a FAQ chatbot. The candidates can do online campaigning, set online rallies and build their profiles for the voters to see. The whole website is secured using a JWT token which ensures that every request made to the website is made by a legitimate and admin verified user. The voter is verified using facial authentication before he is allowed to vote. Our system uses the Eigen-Face algorithm with an accuracy of around 87%.
Keywords
Student Body, MERN Stack, Eigen-face, JWT Token.
Cite as
Akash Maurya, Pooja Shetty, Ganesh Yadava and Leena Ladge, "College Election System using Facial Authentication", In: Saroj Hiranwal and Garima Mathur (eds), Artificial Intelligence and Communication Technologies, SCRS, India, 2022, pp. 501-513. https://doi.org/10.52458/978-81-955020-5-9-48