Vrijendra Singh – författare

COVID-19, a novel coronavirus pandemic has disrupted our society in many ways. Digital healthcare innovations are required more than ever before as we have come across myriad challenges during this pandemic. Scientists and developers are learning and fi nding ways to use artifi cial intelligence applications and natural language processing to comprehend and tackle this disease.

AI technologies are playing an important role in the response to the COVID-19 pandemic. Experts are using all possible tools to study the virus, diagnose individuals, and analyze the public health impacts. This book is a collection of some of the leading efforts related to AI and COVID-19 focused on fi nding how AI can be helpful in monitoring situations from early warnings, swift emergency responses, and critical decision-making. It discusses the use of machine learning and how it may help to reduce the impacts of this pandemic in conjunction with all other research and strategies going on. The book serves as a technical resource of data analytics and AI applications in tracking infectious diseases. It will serve academics, students, data scientists, medical practitioners, and those involved in managing a global pandemic.

Features:

• Directs the attention to the smart digital healthcare system in this COVID-19 pandemic• Simulates novel investigations and how they will be beneficial in understanding the pandemic• Analyses the various issues related to computing, AI apps, big data analytic techniques, and predictive scientifi skill gaps• Explains some interesting and diverse types of challenges and data-driven healthcare applications

COVID-19, a novel coronavirus pandemic has disrupted our society in many ways. Digital healthcare innovations are required more than ever before as we have come across myriad challenges during this pandemic. Scientists and developers are learning and fi nding ways to use artifi cial intelligence applications and natural language processing to comprehend and tackle this disease.

AI technologies are playing an important role in the response to the COVID-19 pandemic. Experts are using all possible tools to study the virus, diagnose individuals, and analyze the public health impacts. This book is a collection of some of the leading efforts related to AI and COVID-19 focused on fi nding how AI can be helpful in monitoring situations from early warnings, swift emergency responses, and critical decision-making. It discusses the use of machine learning and how it may help to reduce the impacts of this pandemic in conjunction with all other research and strategies going on. The book serves as a technical resource of data analytics and AI applications in tracking infectious diseases. It will serve academics, students, data scientists, medical practitioners, and those involved in managing a global pandemic.

Features:

• Directs the attention to the smart digital healthcare system in this COVID-19 pandemic• Simulates novel investigations and how they will be beneficial in understanding the pandemic• Analyses the various issues related to computing, AI apps, big data analytic techniques, and predictive scientifi skill gaps• Explains some interesting and diverse types of challenges and data-driven healthcare applications

We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.

We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.

These two volumes constitute the selected and revised papers presented at the Second International Conference on Communication, Networks and Computing, CNC 2022, held in Gwalior, India, in December 2022. The 53 full papers were thoroughly reviewed and selected from the 152 submissions. They focus on ​the exciting new areas of wired and wireless communication systems, high-dimensional data representation and processing, networks and information security, computing techniques for efficient networks design, vehicular technology and applications and electronic circuits for communication systems that promise to make the world a better place to live in.