An Empirical Analysis on Big Analytics for e-Healthcare and Agriculture

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Abstract

There is a lot being said and done in the field of data analytics. Using large amounts of data for analytics has become one of the rising trends in the business world but, implementing this business intelligence into different sectors of government hasn’t still progressed well. We have discussed two major applications of data analytics in government sectors where the government and eventually the citizens could benefit from all the available big data. The applications include (i) Agriculture, where the big data analytics could result into better crop planning, yield analysis, improved soil health and irrigation as well as reduce the support cost incurred. (ii) The section on data analytics in healthcare mainly points out the importance of predictive analytics in improving personalized healthcare and healthcare infrastructure as a whole. It also talks about how the government can unlock value through big data and machine learning to provide better health insurance than the existing ones and how data analytics is helping with fraud detection while providing the health insurances.

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APA

Purandhar, N., & Ayyasamy, S. (2022). An Empirical Analysis on Big Analytics for e-Healthcare and Agriculture. In Lecture Notes in Electrical Engineering (Vol. 758, pp. 409–417). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-2183-3_40

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