Medical internet of things (IoT)-based applications are being utilized in several industries and have been shown to provide significant advantages to users in critical health applications. Artificial intelligence (AI) plays a key role in the growth and success of medical IoT applications and IoT devices in the medical sector. To enhance revenue, improve competitive advantage, and increase consumer engagement, the use of AI with medical IoT should be encouraged in the healthcare and medical arena. Revolutionizing Healthcare Through Artificial Intelligence and Internet of Things Applications provides greater knowledge of how AI affects healthcare and medical efficacy in order to improve outputs. It focuses on a thorough and comprehensive introduction to machine learning. Covering topics such as patient treatment, cyber-physical systems, and telemedicine, this premier reference source is a dynamic resource for hospital administrators, medical professionals, government officials, students and faculty of higher education, librarians, researchers, and academicians.

This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information. Features: Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications. Investigates privacy-preserving methods with emphasis on data security and privacy. Discusses healthcare scaling and resource efficiency considerations. Examines methods for sharing information among various healthcare organizations while retaining model performance. This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.

This book focuses on the techniques of artificial intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of ethical artificial intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This book explores these challenges, encompassing not only power but also other critical power electronics within vehicles. We aim to introduce innovative approaches, leveraging ethical AI methods, to optimize energy performance in the face of these difficulties. Through this exploration, we seek to provide practical insights into navigating congested VANET environments while upholding ethical principles in technological advancements. Our book will discuss the current power energy concerns faced by vehicles and also contribute a novel strategy to overcome those concerns. The employment of ethical AI in vehicular power energy will undoubtedly improve the effectiveness and production of vehicles.

Online higher education is on the rise, and experienced instructors can play a pivotal role in supporting this key sector by sharing effective, evidence-based practices and strategies. By mentoring less experienced faculty, they can help ensure that online courses are engaging, accessible, and aligned with high academic standards. Their insights are invaluable for building a strong, adaptable online education environment that meets diverse student needs and fosters academic success. Best Practices and Strategies for Online Instructors: Insights From Higher Education Online Faculty serves as a collection of best practices and strategies as described by online faculty working in higher education. It discusses challenges specific to teaching in the online classroom and actionable steps for integrating best practices. Covering topics such as adult online learners, higher education institutions (HEIs), and virtual environments, this book is an excellent resource for higher education faculty, educators, administrators, policymakers, and more.

In the modern era of research, the significance of transdisciplinary and multidisciplinary approaches in enhancing higher education learning outcomes cannot be overlooked. These approaches break down traditional academic silos, fostering a more holistic and interconnected understanding of complex problems. By integrating diverse perspectives and methodologies, they promote critical thinking, creativity, and innovation among students. Educators and institutions must embrace and implement transdisciplinary teaching and technological integration to prepare students for the demands of the future and drive meaningful advancements in education. Transdisciplinary Teaching and Technological Integration for Improved Learning: Case Studies and Practical Approaches embodies a commitment to these approaches, incorporating three cyclical activities—research, participation, and action—that collaboratively seek answers to practical questions through features of participatory and situational research. The book explores problem identification, action planning, observation collection, and behavioral data analysis. Covering topics such as artificial intelligence tools, higher education institutions, and university student satisfaction, this book is an excellent resource for higher education faculty, academic administrators, curriculum developers, educational technology specialists, researchers, and more.

The Healthcare sector is evolving with Healthcare 5.0, promising better patient care and efficiency. However, challenges like data security and analysis arise due to increased digitization. Federated Learning and AI for Healthcare 5.0 offers solutions, explaining cloud computing's role in managing data and advocating for security measures. It explores federated learning's use in maintaining data privacy during analysis, presenting practical cases for implementation. The book also addresses emerging tech like quantum computing and blockchain-based services, envisioning an innovative Healthcare 5.0. It empowers healthcare professionals, IT experts, and data scientists to leverage these technologies for improved patient care and system efficiency, making Healthcare 5.0 secure and patient centric.

The book presents the latest developments in intelligent communication networks based on applicability from various domains of artificial intelligence and machine learning including channel modeling, model-based structure, channel prediction, and signal detection. It further explains important topics such as vehicular mobility modeling, human-centric network applications, security and privacy in social networks, and trust-based intelligent transportation systems. This book: Presents a model-based approach to constructing an effective network by using state-of-the-art artificial intelligent techniques. Discusses the theoretical and practical applications of channel prediction and signal detection. Introduces the fundamental concepts and application of vehicular networks in conjunction with artificial intelligence. Explores wireless communication network techniques enabled by human-centric applications, designed, and developed with artificial intelligence characteristics. Highlights the challenges in designing and developing an effective and intelligent communication network that can be applied in different domains of human activities for finding sustainable solutions. It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer engineering, and information technology.

Intellectual property is a powerful tool in the tourism sector, often acting as a strong commercial ally for industry. Strategies in intellectual property set businesses apart from their competition while promoting national culture and heritage and improving financial status. As tourism and travel become commonplace, businesses and sectors must offer unique opportunities for travelers by marketing their spaces using intellectual ideals, such as ideas, feelings, impressions, and emotions. Further research into intellectual property protection will help businesses stand out in the increasingly competitive tourist industry. Navigating Intellectual Property Challenges in Tourism presents fresh insights into conventional and contemporary paradigms, techniques, and methodologies, as well as more current advancements in research methodology in intellectual property in tourism. It offers solutions for tourism challenges, such as effective trademarks, reputation building, social media branding, and cultural marketing. This book covers topics such as conservation and preservation, global business, and sustainable development, and is a useful resource for business owners, marketing professionals, environmental scientists, researchers, and academicians.

In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success.