Abstract

Rapid incremental growth in population causes the virulence of infectious diseases worldwide. Due to this, health hazards with population growth raise pollution in the air, water, and soil and affect the immunity of individuals. To handle the situation, reliable and easy to reach healthcare services are required. The proliferation of connected technologies along with the Internet of Things (IoT) is providing modern healthcare with extensive care. All-pervading IoT technology gaining a very much attraction nowadays. This paper presents a brief about the E-Health Care System along with its framework. This attempt also presents the ontology approach as data produced by healthcare applications is vast and unstructured which needs to be organized in proper format with a smooth flow of data and also results in less request-response time. Further, this paper discusses the impact of the disease on senior citizens in the current scenario.

Highlights

  • A reliable and prompt E-healthcare system is the immense requirement of today’s scenario

  • The authors mentioned that discrepancies are still present in the current scenario related to the requirement of internet of things (IoT) healthcare services

  • When every device and file used in an IoT healthcare system is represented by ontology and linked together over the web the machine can co-relate and visualize the flow of data, this results in better performance of the system

Read more

Summary

INTRODUCTION

A reliable and prompt E-healthcare system is the immense requirement of today’s scenario. The world is facing a pandemic COVID-19(Coronavirus Disease-19) (Recalcati, 2020) situation and exploring the possibilities to find out the related vaccine as soon as possible. As this disease has symptoms like fever, fatigue, cough, anosmia, ageusia, and human to human transfer, though no standard vaccine has evolved to date. IoMT is a collaboration of medical things and applications to provide connectivity to healthcare systems over the internet. IoT helps to access healthcare data quickly for large scale applications.

LITERATURE REVIEW
Methodology Used
Sensor Layer
Data Preprocessing at Edge
Data Storage
Decision Making

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.