Pandemic Detection and Analysis Through Smart Computing Technologies

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.

這本強大的新書探討了物聯網（IoT）和人工智慧（AI）技術在最近的COVID-19全球大流行期間所扮演的多樣且有時意想不到的角色。該書討論了現有和最新的技術如何在全球衛生危機中應用於多種方式。

《智能計算技術在疫情檢測和分析中的應用》一書的章節探討了病毒檢測、預測、分類、預防和溝通推廣等令人興奮的技術解決方案。該書考慮了病毒的各種傳播方式，以及技術如何應用於個性化醫療系統以及未來疫情的應用。

該書還討論了在疫情期間社交和移動通訊以及網絡的重要性，例如在商業、教育和醫療領域；在研究和開發中；用於健康信息和推廣；在社交生活中等等。其中一章還介紹了使用智能計算進行COVID-19損害預測的時間序列分析。

這本最新的書籍闡明了在COVID-19期間AI、IoT、機器學習和其他技術在面對各種挑戰時的重要角色，以及如何在未來的疫情中加以改進。這本書對於計算機科學和其他領域的專業人士、數據科學家、政府機構和政策制定者、醫生和醫療專業人員、工程師、經濟學家和其他專業人士都具有很高的興趣。這本書對於教師、學生和研究學者來理解這次疫情的前後影響也非常有幫助。

Ram Shringar Raw, PhD, is working in the Department of Computer Science and Engineering of Netaji Subhas University of Technology, East Campus, Delhi, India. He formerly worked as an Associate Professor in the Department of Computer Science, Indira Gandhi National Tribal University (A Central University, MP). He has more than 18 years of teaching, administrative, and research experience. Currently, he is associated with a wide range of journals and conferences as Chief Editor, Editor, Chair, and member. He has guided many MTech and PhD students for their dissertation and thesis. Currently, he is guiding two MTech and four PhD students. His current research interest includes mobile ad hoc networks, vehicular ad hoc networks, and IoT cloud-based networks. Dr. Raw has published two books and more than 100 research papers in international journals and conferences, including those from IEEE, Elsevier. Springer, Wiley & Sons, Taylor & Francis, Inderscience, Hindawi, IERI Letters, American Institute of Physics, etc.

Vishal Jain, PhD, is Associate Professor in the Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, U. P., India. Before that, he has worked for several years as Associate Professor at Bharati Vidyapeeth's Institute of Computer Applications and Management (BVICAM), New Delhi. He has more than 14 years of experience in the academics. He has more than 400 research citation indices with Google Scholar (h-index score 10 and i-10 index 11). He has authored more than 85 research papers in conferences and journals, including the Web of Science and Scopus. He has authored and edited more than 10 books with various reputed publishers, including Springer, Apple Academic Press, CRC, Taylor and Francis Group, Scrivener, Wiley, Emerald, and IGI-Global. His research areas include information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, and sensor networks. He received a Young Active Member Award for the year 2012-13 from the Computer Society of India and a Best Faculty Award for the year 2017 and Best Researcher Award for the year 2019 from BVICAM, New Delhi. He holds PhD (CSE), MTech (CSE), MBA (HR), MCA, MCP and CCNA.

Sanjoy Das, PhD, is Associate Professor and Head, Department of Computer Science, Indira Gandhi National Tribal University (a Central Government University), Amarkantak, M.P. (Manipur Campus), India. Before joining IGNTU he worked as an Associate Professor at the School of Computing Science and Engineering, Galgotias University, India, as well as Assistant Professor. He was also Assistant Professor at G. B. Pant Engineering College, Uttarakhand, and Assam University, Silchar, India. His current research interests include mobile ad hoc networks and vehicular ad hoc networks, distributed systems, and data mining. He has published numerous papers in international journals and conferences, including those associated with IEEE and Springer. He did his BE, MTech, and PhD degrees in Computer Science.

Meenakshi Sharma, PhD, is Dean and Professor in the School of Computer Science & Engineering of the University Center of Research & Development (UCRD) at Galgotias University, Greater Noida, India. She has over 16 years of experience in teaching and research. She is a Senior Member of IEEE and is a highly qualified professional with an MTech in Computer Science & Engineering and a PhD in Computer Science (both from Kurukshetra University). Her research interests are machine learning, image processing, big data analytics, data compression, and digital and data warehousing. She has published over 60 research papers in IEEE Transaction, SCIE, SCI and Scopus in machine learning, deep learning, and AI, in collaboration with international authors. She has published four international grant patents and seven Indian patents. She was awarded a Best Research and Teacher Award in 2017 and 2018. Dr. Sharma has capably guided three PhD candidates and 40+ students in undergraduate/postgraduate programs, with five currently under guidance. She is valuable member of various engineering societies, including ISTE, ACM, InSc, ISDS Society, Japan, IEAE, and many others.

Ram Shringar Raw, 博士，現任印度德里東區Netaji Subhas科技大學計算機科學與工程系的工作。他曾在印度拉賈斯坦邦的Indira Gandhi國家部落大學（一所中央大學）計算機科學系擔任副教授。他擁有超過18年的教學、行政和研究經驗。目前，他擔任多個期刊和會議的主編、編輯、主席和成員。他指導了許多碩士和博士生的論文和論文。目前，他正在指導兩名碩士和四名博士生。他目前的研究興趣包括移動自組網絡、車輛自組網絡和物聯網基於雲的網絡。Raw博士已經出版了兩本書和100多篇國際期刊和會議的研究論文，包括IEEE、Elsevier、Springer、Wiley & Sons、Taylor & Francis、Inderscience、Hindawi、IERI Letters、美國物理學會等。

Vishal Jain, 博士，現任印度Greater Noida的Sharda大學工程與技術學院計算機科學與工程系的副教授。在此之前，他曾在印度新德里的Bharati Vidyapeeth's Institute of Computer Applications and Management（BVICAM）擔任副教授多年。他在學術界擁有超過14年的經驗。他在Google Scholar上擁有超過400個研究引用指數（h指數為10，i-10指數為11）。他在會議和期刊上發表了85多篇研究論文，包括Web of Science和Scopus。他與Springer、Apple Academic Press、CRC、Taylor and Francis Group、Scrivener、Wiley、Emerald和IGI-Global等多個知名出版商合作出版了10多本書籍。他的研究領域包括信息檢索、語義網、本體工程、數據挖掘、自組網絡和感測器網絡。他於2012-13年獲得了印度計算機學會的年度優秀成員獎，並於2017年獲得了BVICAM的最佳教師獎和2019年的最佳研究員獎。他擁有計算機科學的博士學位（CSE），碩士學位（CSE），人力資源管理的MBA，計算機應用的MCA，MCP和CCNA。

Sanjoy Das, 博士，現任印度中央政府的Indira Gandhi國家部落大學（IGNTU）計算機科學系的副教授和系主任，位於印度曼尼普爾邦的Amarkantak。在加入IGNTU之前，他曾在印度Galgotias大學計算機科學與工程學院擔任副教授，並擔任助理教授。他還曾在印度北阿坎德邦的G. B. Pant工程學院和印度Silchar的阿薩姆大學擔任助理教授。他目前的研究興趣包括移動自組網絡和車輛自組網絡、分散系統和數據挖掘。他在國際期刊和會議上發表了許多論文，包括IEEE和Springer相關的論文。他在計算機科學方面獲得了工學士、碩士和博士學位。

Meenakshi Sharma, 博士，現任印度Greater Noida的Galgotias大學研究與發展中心（UCRD）計算機科學與工程學院的院長和教授。她在教學和研究方面擁有超過16年的經驗。她是IEEE的高級會員，是一位高度資深的專業人士，擁有來自Kurukshetra大學的計算機科學與工程的碩士學位和計算機科學的博士學位。她的研究興趣包括機器學習、圖像處理、大數據分析、數據壓縮以及數字和數據倉儲。她與國際作者合作，在機器學習、深度學習和人工智能方面在IEEE Transaction、SCIE、SCI和Scopus等期刊上發表了60多篇研究論文。她申請了四項國際專利和七項印度專利。她在2017年和2018年獲得了最佳研究和教師獎。Sharma博士