Neha Sharma – författare

The book focuses on developments in artificial intelligence (AI) and internet of things (IoT) integration for smart healthcare, with an emphasis on current methodologies and frameworks for the design, growth, implementation, and creative use of such convergence technologies to provide insight into smart healthcare service demands. Concepts like signal recognition, computation, internet of health stuff, and so forth and their applications are covered. Development in connectivity and intelligent networks allowing for social adoption of ambient intelligence is also included.

Features:•Introduces Intelligent IoT as applicable to the key areas of smart healthcare.•Discusses computational intelligence and IoT-based optimizations of smart healthcare systems•Explores effective management of healthcare systems using dedicated IoT-based infrastructures•Includes dedicated chapters on securing patient’s confidential data •Reviews diagnosis of critical diseases from medical imaging using advanced deep learning-based approaches

This book is aimed at researchers, professionals, and graduate students in intelligent systems, big data, cloud computing, information security, and healthcare systems.

The book focuses on developments in artificial intelligence (AI) and internet of things (IoT) integration for smart healthcare, with an emphasis on current methodologies and frameworks for the design, growth, implementation, and creative use of such convergence technologies to provide insight into smart healthcare service demands. Concepts like signal recognition, computation, internet of health stuff, and so forth and their applications are covered. Development in connectivity and intelligent networks allowing for social adoption of ambient intelligence is also included.

Features:•Introduces Intelligent IoT as applicable to the key areas of smart healthcare.•Discusses computational intelligence and IoT-based optimizations of smart healthcare systems•Explores effective management of healthcare systems using dedicated IoT-based infrastructures•Includes dedicated chapters on securing patient’s confidential data •Reviews diagnosis of critical diseases from medical imaging using advanced deep learning-based approaches

This book is aimed at researchers, professionals, and graduate students in intelligent systems, big data, cloud computing, information security, and healthcare systems.

Information and communication technology and the Internet of Things play key roles in smart city projects. It is challenging to handle the large amount of data generated by the different processes related to land use, the environment, the social and economic milieu, energy consumption, and transportation. This book emphasizes that green computing-based infrastructure initiatives benefit not only the environment but the enterprise as well.

Green Computing for Sustainable Smart Cities: A Data Analytics Applications Perspective covers the need for smart green computing from various engineering disciplines and offers diversified applications for such computing with cases studies. The book highlights the sustainable development of smart cities using recent technology and emphasizes advances and cutting-edge techniques throughout. Focused on the different tools, platforms, and techniques associated with smart green computing, this book presents multiple perspectives from academia, industry, and research fields.

The primary audience for this book includes academics, researchers, graduate students, smart city industry practitioners, and city administrators who are engaged in smart cities and related technology.

Information and communication technology and the Internet of Things play key roles in smart city projects. It is challenging to handle the large amount of data generated by the different processes related to land use, the environment, the social and economic milieu, energy consumption, and transportation. This book emphasizes that green computing-based infrastructure initiatives benefit not only the environment but the enterprise as well.

Green Computing for Sustainable Smart Cities: A Data Analytics Applications Perspective covers the need for smart green computing from various engineering disciplines and offers diversified applications for such computing with cases studies. The book highlights the sustainable development of smart cities using recent technology and emphasizes advances and cutting-edge techniques throughout. Focused on the different tools, platforms, and techniques associated with smart green computing, this book presents multiple perspectives from academia, industry, and research fields.

The primary audience for this book includes academics, researchers, graduate students, smart city industry practitioners, and city administrators who are engaged in smart cities and related technology.

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately.

Features:

This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately.

Features:

This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.

The industrial landscape is changing rapidly, and so is global society. This change is driven by the growing adoption of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies. IIoT and AI are transforming the way industrial engineering is done, enabling new levels of automation, productivity, and efficiency. However, as IIoT and AI become more pervasive in the industrial world, they also offer new security risks that must be addressed to ensure the reliability and safety of critical systems.

Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments provides a comprehensive guide to IIoT security, covering topics such as network architecture, risk management, data security, and compliance. It addresses the unique security challenges that the cloud and edge environments pose, providing practical guidance for securing IIoT networks in these contexts. It includes numerous real-world case studies and examples, providing readers with practical insights into how IIoT security and AI-enabled industrial engineering are being implemented in various industries. Best practices are emphasized for the readers to ensure the reliability, safety, and security of their systems while also learning the latest developments in IIoT security for AI-enabled industrial engineering systems in this rapidly evolving field.

By offering step-by-step guidance for the implantation process along with best practices, this book becomes a valuable resource for practitioners and engineers in the areas of industrial engineering, IT, computer engineering, and anyone looking to secure their IIoT network against cyber threats.

The industrial landscape is changing rapidly, and so is global society. This change is driven by the growing adoption of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies. IIoT and AI are transforming the way industrial engineering is done, enabling new levels of automation, productivity, and efficiency. However, as IIoT and AI become more pervasive in the industrial world, they also offer new security risks that must be addressed to ensure the reliability and safety of critical systems.

Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments provides a comprehensive guide to IIoT security, covering topics such as network architecture, risk management, data security, and compliance. It addresses the unique security challenges that the cloud and edge environments pose, providing practical guidance for securing IIoT networks in these contexts. It includes numerous real-world case studies and examples, providing readers with practical insights into how IIoT security and AI-enabled industrial engineering are being implemented in various industries. Best practices are emphasized for the readers to ensure the reliability, safety, and security of their systems while also learning the latest developments in IIoT security for AI-enabled industrial engineering systems in this rapidly evolving field.

By offering step-by-step guidance for the implantation process along with best practices, this book becomes a valuable resource for practitioners and engineers in the areas of industrial engineering, IT, computer engineering, and anyone looking to secure their IIoT network against cyber threats.

The built environment is undergoing a profound transformation driven by the integration of cutting-edge geospatial technologies. Smart Buildings and Cities with Remote Sensing and GIS serves as a comprehensive guide to navigating this transformation and bridges the gap between traditional architectural and planning practices and the innovative possibilities of remote sensing (RS) and geographic information systems (GIS).

The book demonstrates how architects, planners, and decisionmakers can use GIS and RS to design smarter, context-aware, and eco-friendly urban spaces. It explores innovative approaches for architecture, focusing on geospatial site analysis, net-zero energy building designs, heritage preservation, innovative virtual campus planning methodologies and even futuristic concepts like habitat design on the lunar surface.

Key features:

• Brings together contemporary geospatial technologies and their applications to address the challenges and opportunities in designing smart buildings and cities.

• Provides actionable solutions for professionals, researchers, and policymakers.

• Includes global contributions that provide diverse perspectives on smart city and building applications.

• Highlights how geospatial data-driven insights can revolutionize decisionmaking processes in urban planning and building design.

The work is designed for postgraduate students and researchers in the departments of architecture, planning, and geomatics, geoinformatics, software engineering.

The built environment is undergoing a profound transformation driven by the integration of cutting-edge geospatial technologies. Smart Buildings and Cities with Remote Sensing and GIS serves as a comprehensive guide to navigating this transformation and bridges the gap between traditional architectural and planning practices and the innovative possibilities of remote sensing (RS) and geographic information systems (GIS).

The book demonstrates how architects, planners, and decisionmakers can use GIS and RS to design smarter, context-aware, and eco-friendly urban spaces. It explores innovative approaches for architecture, focusing on geospatial site analysis, net-zero energy building designs, heritage preservation, innovative virtual campus planning methodologies and even futuristic concepts like habitat design on the lunar surface.

Key features:

• Brings together contemporary geospatial technologies and their applications to address the challenges and opportunities in designing smart buildings and cities.

• Provides actionable solutions for professionals, researchers, and policymakers.

• Includes global contributions that provide diverse perspectives on smart city and building applications.

• Highlights how geospatial data-driven insights can revolutionize decisionmaking processes in urban planning and building design.

The work is designed for postgraduate students and researchers in the departments of architecture, planning, and geomatics, geoinformatics, software engineering.

The book analyzes the combination of intelligent data analytics with the intricacies of biological data that has become a crucial factor for innovation and growth in the fast-changing field of bioinformatics and biomedical systems.

Intelligent Data Analytics for Bioinformatics and Biomedical Systems delves into the transformative nature of data analytics for bioinformatics and biomedical research. It offers a thorough examination of advanced techniques, methodologies, and applications that utilize intelligence to improve results in the healthcare sector. With the exponential growth of data in these domains, the book explores how computational intelligence and advanced analytic techniques can be harnessed to extract insights, drive informed decisions, and unlock hidden patterns from vast datasets. From genomic analysis to disease diagnostics and personalized medicine, the book aims to showcase intelligent approaches that enable researchers, clinicians, and data scientists to unravel complex biological processes and make significant strides in understanding human health and diseases.

This book is divided into three sections, each focusing on computational intelligence and data sets in biomedical systems. The first section discusses the fundamental concepts of computational intelligence and big data in the context of bioinformatics. This section emphasizes data mining, pattern recognition, and knowledge discovery for bioinformatics applications. The second part talks about computational intelligence and big data in biomedical systems. Based on how these advanced techniques are utilized in the system, this section discusses how personalized medicine and precision healthcare enable treatment based on individual data and genetic profiles. The last section investigates the challenges and future directions of computational intelligence and big data in bioinformatics and biomedical systems. This section concludes with discussions on the potential impact of computational intelligence on addressing global healthcare challenges.

Audience

Intelligent Data Analytics for Bioinformatics and Biomedical Systems is primarily targeted to professionals and researchers in bioinformatics, genetics, molecular biology, biomedical engineering, and healthcare. The book will also suit academicians, students, and professionals working in pharmaceuticals and interpreting biomedical data.

The book analyzes the combination of intelligent data analytics with the intricacies of biological data that has become a crucial factor for innovation and growth in the fast-changing field of bioinformatics and biomedical systems.

Intelligent Data Analytics for Bioinformatics and Biomedical Systems delves into the transformative nature of data analytics for bioinformatics and biomedical research. It offers a thorough examination of advanced techniques, methodologies, and applications that utilize intelligence to improve results in the healthcare sector. With the exponential growth of data in these domains, the book explores how computational intelligence and advanced analytic techniques can be harnessed to extract insights, drive informed decisions, and unlock hidden patterns from vast datasets. From genomic analysis to disease diagnostics and personalized medicine, the book aims to showcase intelligent approaches that enable researchers, clinicians, and data scientists to unravel complex biological processes and make significant strides in understanding human health and diseases.

This book is divided into three sections, each focusing on computational intelligence and data sets in biomedical systems. The first section discusses the fundamental concepts of computational intelligence and big data in the context of bioinformatics. This section emphasizes data mining, pattern recognition, and knowledge discovery for bioinformatics applications. The second part talks about computational intelligence and big data in biomedical systems. Based on how these advanced techniques are utilized in the system, this section discusses how personalized medicine and precision healthcare enable treatment based on individual data and genetic profiles. The last section investigates the challenges and future directions of computational intelligence and big data in bioinformatics and biomedical systems. This section concludes with discussions on the potential impact of computational intelligence on addressing global healthcare challenges.

Audience

Intelligent Data Analytics for Bioinformatics and Biomedical Systems is primarily targeted to professionals and researchers in bioinformatics, genetics, molecular biology, biomedical engineering, and healthcare. The book will also suit academicians, students, and professionals working in pharmaceuticals and interpreting biomedical data.