Aumbs: Aadhaar And Unique Multimodal Based Biometric System For E-Voting Using Ianfis Method

A vote is one of the basic human rights of any person in a democratic nation. By exercising the right to vote, individuals appoint the best leader to guide them. In order to exercise this independence, virtually all election programs include previous measures: electoral identification and recognition, voting and recording of ballots, counting of votes, and posting of election results. During the voting system, which is central to the e-voting system, voter identification and security are required. Therefore, the need to design a secure e-voting system is very important. A secure electronic voting system that uses a unique ID number, ie aadhaar amount. Creating a set of metrics to identify unusual customer habits by recognizing their client and cognitive characteristics is a significant problem. In this work, additional security is used to replace these problems with the Aadhaar Multi-Model Biometric Range with Cognitive Characteristic Detection. When participating in elections, election recognition can be done using multimodal biometric models such as the head, iris, finger, palm print, finger nerve, ear, and seal. If the voter's biometric data matches the Aadhaar database, the individual is allowed to place their ballot. Coupling is done using the proposed new classification system, the Advanced Adaptive Neuro-Fuzzy Inference System (IANFIS). Recommended Plan is a highly electronic, technology based and guaranteed program.