Massive Data Processing Using Mapreduce Aggregation To Make Digitized India

Abstract

Digitized India is used to connect rural areas with high speed Internet. As a result, it is used to reduce crime, manual power, documentation and also increases the job opportunities. Nowadays people are facing many problems when they forget to carry the driving license and also to reduce the corruption, the proposed system combines the driving license with Aadhar card. The details of driving license and Aadhar card data can be combined using the MapReduce Counters. It automatically aggregated over Map and Reduce phases. It is used to create a tool that manages the handling of license using unique identification associated with each individual. It helps the user to travel various places without having the license. So the proposed system will make the digitization of data on a large scale for easy and quick access throughout the India. Sqoop is a tool intended to exchange information amongst Hadoop and social databases. Sqoop utilizes MapReduce to import and export the information, which gives parallel operation and in addition adaptation to noncritical failure. As the result of parallel operations time utilization for transferring the data get decreased radically.

IoT Enabled Visual Recognition Model for Biometric Authentication

“…According to the Indian statistics the total number of aadhar card holders in India 89% in the total population. And also people records are digitized [7][8][9]. These biological data is unique can be used for other applications like public surveillance, crowed monitoring, socio and personal Psychological behavioral monitoring etc.…”