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Proceedings ArticleDOI

De-duplication of passports using Aadhaar

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TLDR
A case study on the existing de-duplication methods for passport enrolments and other such documents and helps identify big and fast data platforms to identify such e-governance plans, by evaluating the accuracy and efficiency of existing algorithms.
Abstract
Big data is an emerging technology that is becoming an essential part of national governance. Aadhaar is the unique identification scheme of India, handled by the Unique Identification Authority of India (UIDAI), which deals with big data. Every person above the age of 5 years has to register their demographic details (Name, Date of Birth, Address and Phone number) and biometric details (10 fingerprints and both iris) and then these details are used to verify the authenticity of the person when any services are required by him. Passport is a legal document that is carried by a person when he travels between countries, but in the case of the older passports with no biometric data, a person may have more than one legal passport with different demographic details. This paper does a case study on the existing de-duplication methods for passport enrolments and other such documents. In the case of newer passports, it takes 10 days to link with Aadhaar at the time of registration, hence the aim is to reduce the processing time of the linking and verification. String matching algorithms are used to compare the demographics, and techniques such as genetic programming and hashing are used for de-duplication. This case study also helps identify big and fast data platforms to identify such e-governance plans, by evaluating the accuracy and efficiency of existing algorithms. This system aims to predict the duplication of passports by linking Aadhaar and passport details, and to reduce the processing time of the Aadhaar database by using parallel algorithms.

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Book ChapterDOI

Melanoma Detection Using HSV with SVM Classifier and De-duplication Technique to Increase Efficiency

TL;DR: Proposed de-duplication method will help in image preprocessing time which will also help in detection of melanoma, and KNN, Naïve Bayes and SVM classifier are used for training and testing purpose, SVM shows the highest accuracy of classifier with de- duplication techniques.
Book ChapterDOI

Smart Voting System with GSM Module

Nicola Greco
TL;DR: In this article , a methodology is explained which verifies every voter with their respective IDs and the existing database using biometrics and provide the voters with their voting status through an SMS to the registered number.
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