Gitanjali R. Shinde – författare

VANET (vehicular ad hoc network) is a subgroup of MANET (mobile ad hoc network). It enables communication among vehicles on the road and between related infrastructures. This book addresses the basic elements of VANET along with components involved in the communication with their functionalities and configurations. It contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms, and protocols, and addresses the different services provided by VANET with the help of a scenario showing a network tackling an emergency.Features:• Covers all important concepts of VANET for beginners and different road scenarios in VANET• Covers essential communication protocols in VANET• Introduces approaches for VANET implementation using simulators• Provides a classification of messages and a priority-based message forwarding strategyThis book is aimed at undergraduates, postgraduates, industry, researchers, and research scholars in information and communications technology.

VANET (vehicular ad hoc network) is a subgroup of MANET (mobile ad hoc network). It enables communication among vehicles on the road and between related infrastructures. This book addresses the basic elements of VANET along with components involved in the communication with their functionalities and configurations. It contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms, and protocols, and addresses the different services provided by VANET with the help of a scenario showing a network tackling an emergency.Features:• Covers all important concepts of VANET for beginners and different road scenarios in VANET• Covers essential communication protocols in VANET• Introduces approaches for VANET implementation using simulators• Provides a classification of messages and a priority-based message forwarding strategyThis book is aimed at undergraduates, postgraduates, industry, researchers, and research scholars in information and communications technology.

With the ever-increasing use of AI technologies, ethical considerations take on greater importance. Human-centric AI emphasizes transparency, making sure that AI systems work in a way that users can comprehend and trust. Additionally, it addresses bias and discrimination issues, ensuring fairness and inclusion in the design and implementation of AI apps. By emphasizing user experience, security, and human-centric AI, the goal is to improve collaboration between people and machines, rather than replacing human decisions, creating a future where technology is a force for good, benefiting both businesses and society. Written from a technological point of view, Industry 5.0 for Society 5.0 explores the impact of cutting-edge technologies, including the Internet of Things, cloud, artificial intelligence, and digital twin, on individuals and community, and considers how they can be used to solve societal problems. The book considers how these technologies can positively affect industry, healthcare, agriculture, design and manufacture, contributing to the development of a sustainable environment that ultimately creates a positive and mutually beneficial relationship between people and AI.Presents the fundamentals, challenges and advancements in AI required for Industry 5.0 to be beneficial to societyFocuses on human-centric AI and how it can be used to create more sustainable industryExplores the ethical considerations and regulatory aspects of Edge AI, helping readers navigate the responsible use of this technology

This book focuses on various authorization and access control techniques, threats and attack modeling, including an overview of the Open Authorization 2.0 (OAuth 2.0) framework along with user-managed access (UMA) and security analysis. Important key concepts are discussed regarding login credentials with restricted access to third parties with a primary account as a resource server. A detailed protocol overview and authorization process, along with security analysis of OAuth 2.0, are also discussed in the book. Case studies of websites with vulnerability issues are included.FEATURES Provides an overview of the security challenges of IoT and mitigation techniques with a focus on authorization and access control mechanisms Discusses a behavioral analysis of threats and attacks using UML base modeling Covers the use of the OAuth 2.0 Protocol and UMA for connecting web applications Includes role-based access control (RBAC), discretionary access control (DAC), mandatory access control (MAC) and permission-based access control (PBAC) Explores how to provide access to third-party web applications through a resource server by use of a secured and reliable OAuth 2.0 frameworkThis book is for researchers and professionals who are engaged in IT security, auditing and computer engineering.

This book focuses on various authorization and access control techniques, threats and attack modeling, including an overview of the Open Authorization 2.0 (OAuth 2.0) framework along with user-managed access (UMA) and security analysis. Important key concepts are discussed regarding login credentials with restricted access to third parties with a primary account as a resource server. A detailed protocol overview and authorization process, along with security analysis of OAuth 2.0, are also discussed in the book. Case studies of websites with vulnerability issues are included.FEATURES Provides an overview of the security challenges of IoT and mitigation techniques with a focus on authorization and access control mechanisms Discusses a behavioral analysis of threats and attacks using UML base modeling Covers the use of the OAuth 2.0 Protocol and UMA for connecting web applications Includes role-based access control (RBAC), discretionary access control (DAC), mandatory access control (MAC) and permission-based access control (PBAC) Explores how to provide access to third-party web applications through a resource server by use of a secured and reliable OAuth 2.0 frameworkThis book is for researchers and professionals who are engaged in IT security, auditing and computer engineering.

This book explores the need for a data‑centric AI approach and its application in the multidisciplinary domain, compared to a model‑centric approach. It examines the methodologies for data‑centric approaches, the use of data‑centric approaches in different domains, the need for edge AI and how it differs from cloud‑based AI. It discusses the new category of AI technology, "data‑centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‑centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods.• Includes a collection of case studies with experimentation results to adhere to the practical approaches• Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways• Discusses methodologies to achieve accurate results by improving the quality of data• Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications

This book explores the need for a data‑centric AI approach and its application in the multidisciplinary domain, compared to a model‑centric approach. It examines the methodologies for data‑centric approaches, the use of data‑centric approaches in different domains, the need for edge AI and how it differs from cloud‑based AI. It discusses the new category of AI technology, "data‑centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‑centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods.• Includes a collection of case studies with experimentation results to adhere to the practical approaches• Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways• Discusses methodologies to achieve accurate results by improving the quality of data• Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications

This book covers all small details about Underwater Sensor Networks (UWSN). Researchers can use this book as a prerequisite before starting any research on underwater networks or underwater applications.

This book extends the work from introduction of ubiquitous computing, to the Internet of things to security and to privacy aspects of ubiquitous computing. The main endeavour of this book is threat analysis and activity modelling of attacks in order to give anactual view of the ubiquitous computing applications.

This book extends the work from introduction of ubiquitous computing, to the Internet of things to security and to privacy aspects of ubiquitous computing. The main endeavour of this book is threat analysis and activity modelling of attacks in order to give anactual view of the ubiquitous computing applications.

This book presents cognitive modeling along with the new paradigm machine thinking to enhance existing AI power and address its current limitations. This book provides overview of natural and artificial intelligence along with the computing models used currently. The need of advancing the current models is presented with suitable examples. The business case studies presented in different domains provide possible use of augmented intelligence with the proposed machine thinking paradigm. This book is targeted at academicians, researchers, students, professionals who belong to disciplines which involves intelligent computing and modelling human thinking. It provides possible multidisciplinary research directions including social psychology, artificial intelligence, HCI, cognition for applications in various domains.

This book presents cognitive modeling along with the new paradigm machine thinking to enhance existing AI power and address its current limitations. The business case studies presented in different domains provide possible use of augmented intelligence with the proposed machine thinking paradigm.

This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.

This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI.