SN Computer Science (2021) 2:334
334 Page 8 of 24
SN Computer Science
India (UIDAI) which aims to manage and maintain India’s
Aadhaar citizen registry [
20
,
37
]. The key factor in Aadhaar
is the collection of personal information from citizens. Such
information include iris retinal scans, fingerprints, residen-
tial
addresses, and digital face registrations. All these are
clustered and maintained by MapR, an enterprise-grade
NoSQL database in Hadoop. MapR is used due to its high-
speed
data verification performance, i.e., within 200 ms, 3–5
MB of individual data are obtained from people, processed
and mapped to the database to get the exact evaluation
results. This software-based data entity works on the Hadoop
platform and uses big data analytical
algorithms for the pro-
cessing and analysis [
37
]. To obtain meaningful outcomes
from the captured data, large and complex programs were
developed. These algorithms evaluate the consumer personal
data both statistically and visually
depending on the require-
ments, thus parallel computing is crucial for this scenario.
Big data programs have the potential for parallel comput-
ing and data visualization, making the analytical framework
easily interpretable by all domestic consumer entities upon
proper government approval. The proliferation
of contactless
consumer electronics that use image recognition software,
sensor-based encryption, and pattern mode decoding require
big data storage infrastructures and processing power for
essential computations.
