Today, computation is an essential component of every technology. However, there has not been much research on quantum computing, even though it has the capability to solve complex problems in an efficient way. Further study is required to fully understand the uses and benefits of this technology. The Handbook of Research on Quantum Computing for Smart Environments presents investigating physical realizations of quantum computers, encoders, and decoders, including photonic quantum realization, cavity quantum electrodynamics, and many more topics on Bits to Qubits. Covering key topics such as machine learning, software, quantum algorithms, and neural networks, this major reference work is ideal for engineers, computer scientists, physicists, mathematicians, researchers, academicians, scholars, practitioners, instructors, and students.

AUTOMATED SECURE COMPUTING FOR NEXT-GENERATION SYSTEMS This book provides cutting-edge chapters on machine-empowered solutions for next-generation systems for today’s society. Security is always a primary concern for each application and sector. In the last decade, many techniques and frameworks have been suggested to improve security (data, information, and network). Due to rapid improvements in industry automation, however, systems need to be secured more quickly and efficiently. It is important to explore the best ways to incorporate the suggested solutions to improve their accuracy while reducing their learning cost. During implementation, the most difficult challenge is determining how to exploit AI and ML algorithms for improved safe service computation while maintaining the user’s privacy. The robustness of AI and deep learning, as well as the reliability and privacy of data, is an important part of modern computing. It is essential to determine the security issues of using AI to protect systems or ML-based automated intelligent systems. To enforce them in reality, privacy would have to be maintained throughout the implementation process. This book presents groundbreaking applications related to artificial intelligence and machine learning for more stable and privacy-focused computing. By reflecting on the role of machine learning in information, cyber, and data security, Automated Secure Computing for Next-Generation Systems outlines recent developments in the security domain with artificial intelligence, machine learning, and privacy-preserving methods and strategies. To make computation more secure and confidential, the book provides ways to experiment, conceptualize, and theorize about issues that include AI and machine learning for improved security and preserve privacy in next-generation-based automated and intelligent systems. Hence, this book provides a detailed description of the role of AI, ML, etc., in automated and intelligent systems used for solving critical issues in various sectors of modern society. Audience Researchers in information technology, robotics, security, privacy preservation, and data mining. The book is also suitable for postgraduate and upper-level undergraduate students.

Academics 4.0 has become increasingly crucial in recent times due to the impact of Industry 4.0 on various fields. The emergence of disruptive technologies and the cyber-physical world has underscored the need for experts in these areas, which requires proper training of students from an early stage. Education 4.0 is essential in preparing faculties and students adequately for this purpose. This approach shifts the focus from teaching to learning and employs blended learning, MOOC courses, and flipped classrooms to achieve better understanding and application of knowledge. The practical aspect of the subject is discussed in the classroom, while the theoretical aspect is taught outside the class. The book, Architecture and Technological Advancements of Education 4.0, aims to explain the rationale, advantages, and features of Academics 4.0, explore assessment tools and techniques, and describe the national policy for bringing change in education. It also covers blended learning, MOOC courses, virtual labs, and mobile learning, with a focus on their benefits. The book will be useful for universities and educational entities that aim to follow Academics 4.0 in the education system, serve as a reference manual for research articles, and be helpful to faculties and academicians who wish to implement and assess online techniques. Additionally, it will be an excellent learning platform for providers and users of relevant domains, with a broad range of topics covering its impact on the education system, students, and workforce.

PRIVACY PRESERVATION of GENOMIC and MEDICAL DATA Discusses topics concerning the privacy preservation of genomic data in the digital era, including data security, data standards, and privacy laws so that researchers in biomedical informatics, computer privacy and ELSI can assess the latest advances in privacy-preserving techniques for the protection of human genomic data. Privacy Preservation of Genomic and Medical Data focuses on genomic data sources, analytical tools, and the importance of privacy preservation. Topics discussed include tensor flow and Bio-Weka, privacy laws, HIPAA, and other emerging technologies like Internet of Things, IoT-based cloud environments, cloud computing, edge computing, and blockchain technology for smart applications. The book starts with an introduction to genomes, genomics, genetics, transcriptomes, proteomes, and other basic concepts of modern molecular biology. DNA sequencing methodology, DNA-binding proteins, and other related terms concerning genomes and genetics, and the privacy issues are discussed in detail. The book also focuses on genomic data sources, analyzing tools, and the importance of privacy preservation. It concludes with future predictions for genomic and genomic privacy, emerging technologies, and applications. Audience Researchers in information technology, data mining, health informatics and health technologies, clinical informatics, bioinformatics, security and privacy in healthcare, as well as health policy developers in public and private health departments and public health.

Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence—or soft computing—is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information. - Brings together quantum computing with computational intelligence to achieve enhanced performance and robust solutions - Includes numerous case studies, tools, and technologies to apply the concepts to real world practice - Provides the missing link between the research and practice

The recent advancements in the field of the internet of things (IoT), AI, big data, blockchain, augmented reality (AR)/virtual reality (VR), cloud platforms, quantum computing, cybersecurity, and telecommunication technology enabled the promotion of conventional computer-aided industry to the metaverse ecosystem that is powered by AR/VR-driven technologies. In this paradigm shift, the integrated technologies of IoT and AI play a vital role to connect the cyberspace of computing systems and virtual environments. AR/VR supports a huge range of industrial applications such as logistics, the food industry, and manufacturing utilities. AI-Based Technologies and Applications in the Era of the Metaverse discusses essential components of the metaverse ecosystem such as concepts, methodologies, technologies, modeling, designs, statistics, implementation, and maintenance. Covering key topics such as machine learning, deep learning, quantum computing, and blockchain, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

The security of assistive systems in AI-based digital health communication is a critical challenge, leaving users vulnerable to threats and attacks. AI-Based Digital Health Communication for Securing Assistive Systems provides a comprehensive solution by integrating artificial intelligence (AI) with cybersecurity measures. Edited by Vijeyananthan Thayananthan, this groundbreaking book equips assistive technology developers, researchers, and professionals with the knowledge and tools necessary to safeguard these systems and protect user privacy and well-being. Covering topics such as assistive communication technology, secure assistive technologies, robotics, and AI-based eHealth applications, the book explores innovative approaches to enhance the security of assistive systems. It offers practical guidance and insights into the strategic role of AI-based cybersecurity, empowering readers to protect individuals relying on assistive systems. Professionals, researchers, and scholars in the field of digital health communication will find this book invaluable, especially assistive technology developers looking to enhance their understanding of AI-based cybersecurity. Postgraduate students, research scientists, and academic research scholars will also benefit from the book's valuable insights and advancements. Executives and healthcare management professionals involved in digital health communication can leverage the book's expertise to drive organizational development and create a safer environment for individuals dependent on assistive systems.