Using big data for predicting alerts for epidemics in rural areas and in generating climactic forecasts

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Monideepa Roy

Kalinga Institute of Industrial Technology, India

: J Comput Eng Inf Technol

Abstract

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Big data is one of the most phenomenal topics in current years and has found a wide variety of applications. One of them
is using big data for forecasting certain incidents by using various prediction mechanisms and statistical tools over raw
data. Two such applications are firstly, predicting the onset of a disease epidemic in a rural area based on the symptoms of its
inhabitants, and secondly developing more accurate weather forecasting and warning mechanisms. It is applicable in the first
case, since most villages especially in the Indian scenario suffer from lack of access to proper medical care and monitoring.
Moreover, due to lack of awareness, predicting a disease epidemic in time and containing its spreading is crucial in saving many
lives. I would like to present a framework we have developed for such a system. The second case is using environmental data to
predict various weather conditions like cyclone warnings, heat or cold waves, floods etc. Since the Indian subcontinent relies
heavily on the climatic conditions for its crops, more accurate predictions and warning will assist the farmers in making the
correct decisions. Both the systems need to process huge amounts of data to effectively arrive at the conclusions. My talk will
be revolving around the two areas of applications, the frameworks used and the issues, advantages and challenges.

Biography

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