Surveillance of type -I & II diabetic subjects on physical characteristics: IoT and big data perspective in healthcare @ NCR, India

6Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The Delhi and NCR healthcare systems are rapidly registering electronic health records, diagnostic information available electronically. Furthermore, clinical analysis is rapidly advancing-large quantities of information are examined and new insights are part of the analysis of this technology-experienced as Big Data. It provides tools for storing, managing, studying, and assimilating large amounts of robust, structured and unstructured data generated by existing medical organizations. Recently, data analysis data have been used to help provide care and diagnose disease. In the current era, systems need connected devices, people, time, places and networks that are fully integrated on the Internet (IoT). The Internet has become new in developing health monitoring systems. Diabetes is defined as a group of metabolic disorders affecting human health worldwide. Extensive research (diagnosis, path physiology, treatment, etc.) produces a great deal of data on all aspects of diabetes. The main purpose of this chapter is to provide a detailed analysis of healthcare using large amounts of data and analysis. From the Hospitals of Delhi and NCR, sample of 30 subjects has been collected in random fashion who has been suffering from Diabetes from their Health Insurance Providers without disclosing any Personal Information (PI) or Sensitive Personal Information (SPI) by Law. The present study aimed to analyze diabetes with the latest IoT and Big Data analysis techniques and it’s correlation with stress (TTH) on human health. Authors have tried to include age, gender & insulin factor and its correlation with diabetes. Overall, In conclusion, TTH cases increasing with age in case of males and not following the pattern of diabetes variation with age while in case of female TTH pattern variation is same as diabetes i.e. increasing trend up to age of 60 then decreasing.

Cite

CITATION STYLE

APA

Rastogi, R., Chaturvedi, D. K., Satya, S., Arora, N., Singhal, P., & Gupta, M. (2020). Surveillance of type -I & II diabetic subjects on physical characteristics: IoT and big data perspective in healthcare @ NCR, India. In Internet of Things (IoT): Concepts and Applications (pp. 429–460). Springer International Publishing. https://doi.org/10.1007/978-3-030-37468-6_23

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free