Edge intelligence to smart management and control of epidemic

Title

Edge intelligence to smart management and control of epidemic

Creator

Nanjundan P.; George J.P.; Karpagam C.

Description

The effects of COVID-19 vary from person to person. A pandemic is devastating economically and socially. Thousands of enterprises face the possibility of collapse. More than half of the world's 3.3 billion workers may lose their livelihoods if the current crisis continues. The world's healthcare services are facing an unprecedented situation due to the recent outbreak of a novel coronavirus (COVID-19). Community and government health are adversely affected by the COVID-19 pandemic. COVID-19 has continued to spread, and mortalities have risen steadily. The spread of this disease can therefore be controlled utilizing nonpharmacological methods, such as quarantine, isolation, and public health education. Recent breakthroughs in deep learning (DL) have led to an explosion in applications and services relating to artificial intelligence (AI). The rapid advancements in mobile computing and AI have enabled zillions of Bytes of data to be generated at the network edge from thousands of mobile devices and internet of things (IoT) devices connected to the Internet. As a result of the success of IoT and AI technologies, it is of utmost importance that we expand the AI frontiers to the network edge in order for big data to be fully tapped. Edge computing (EC) can help overcome this trend because it allows computation-intensive AI applications to run on edge hardware. The topic of discussion in this chapter is edge intelligence (EI) technology's application in limiting virus spread during pandemics. 2024 Apple Academic Press, Inc. All rights reserved.

Source

Reconnoitering the Landscape of Edge Intelligence in Healthcare, pp. 175-190.

Date

2024-01-01

Publisher

Apple Academic Press

Subject

Artificial intelligence; Computational intelligence; Edge computing; Edge COVID-19; Edge intelligence; Internet of things; Smart healthcare

Coverage

Nanjundan P., Department of Data Science, Christ University, Lavasa, Pune, Maharashtra, India; George J.P., Department of Data Science, Christ University, Lavasa, Pune, Maharashtra, India; Karpagam C., Department of Computer Science with Data Analytics, Dr. N.G.P. Arts and Science College, Tamil Nadu, India

Rights

Restricted Access

Relation

ISBN: 978-100089493-6; 978-177491436-6

Format

Online

Language

English

Type

Book chapter

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185138985&partnerID=40&md5=bfda0d0c3c38958c5263159c0b037f91