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Book synopsis

This powerful new volume explores the diverse and sometimes unexpected roles that IoT and AI technologies played during the recent COVID-19 global pandemic. The book discusses the how existing and new state-of-the art technology has been and can be applied for global health crises in a multitude of ways.

The chapters in Pandemic Detection and Analysis through Smart Computing Technologies look at exciting technological solutions for virus detection, prediction, classification, prevention, and communication outreach. The book considers the various modes of transmission of the virus as well as how technology has been implemented for personalized healthcare systems and how it can be used for future pandemics.

The huge importance of social and mobile communication and networks during the pandemic is addressed such as in business, education, and healthcare; in research and development; for health information and outreach; in social life; and more. A chapter also addresses using smart computing for forecasting the damage caused by COVID-19 using time series analyses.

This up-to-the-minute volume illuminates on the many ways AI, IoT, machine learning, and other technologies have important roles in the diverse challenges faced during COVID-19 and how they can be enhanced for future pandemic situations. The volume will be of high interest to those in different fields of computer science and other domains as well as to data scientists, government agencies and policymakers, doctors and healthcare professionals, engineers, economists, and many other professionals. This book will also be very helpful to faculty, students, and research scholars in understanding the pre- and post-effect of this pandemic.

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Medizin Nichtklinische Fächer

• Full title: Pandemic Detection and Analysis Through Smart Computing Technologies
• Author: Ram Shringar Raw, Vishal Jain, Sanjoy Das
• Language: English
• Binding: Hardback
• Number of pages: 310
• EAN: 9781774910320
• ISBN: 1774910322
• ID: 38906571
• Publisher: Apple Academic Press Inc.
• Weight: 766 g
• Dimensions: 229 × 152 mm
• Date of publishing: 07. July 2022

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