This book contains high-quality and original research on computational intelligence for green smart cities research. In recent years, the use of smart city technology has rapidly increased through the successful development and deployment of Internet of Things (IoT) architectures. The citizens' quality of life has been improved in several sensitive areas of the city, such as transportation, buildings, health care, education, environment, and security, thanks to these technological advances Computational intelligence techniques and algorithms enable a computational analysis of enormous data sets to reveal patterns that recur. This information is used to inform and improve decision-making at the municipal level to build smart computational intelligence techniques and sustainable cities for their citizens. Machine intelligence allows us to identify trends (patterns). The smart city could better integrate its transportation network, for example. By offering a better public transportation network adapted to the demand, we could reduce personal vehicles and energy consumption. A smart city could use models to predict the consequences of a change, such as pedestrianizing a street or adding a bike lane. A city can even create a 3D digital twin to test hypothetical projects. This book comprises many state-of-the-art contributions from scientists and practitioners working in machine intelligence and green smart cities. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances in machine intelligence for green and sustainable smart city applications.

This book introduces and presents the newest up-to-date methods, approaches and technologies on how to detect child cyberbullying on social media as well as monitor kids E-learning, monitor games designed and social media activities for kids. On a daily basis, children are exposed to harmful content online. There have been many attempts to resolve this issue by conducting methods based on rating and ranking as well as reviewing comments to show the relevancy of these videos to children; unfortunately, there still remains a lack of supervision on videos dedicated to kids. This book also introduces a new algorithm for content analysis against harmful information for kids. Furthermore, it establishes the goal to track useful information of kids and institutes detection of kid’s textual aggression through methods of machine and deep learning and natural language processing for a safer space for children on social media and online and to combat problems, such as lack of supervision, cyberbullying, kid’s exposure to harmful content. This book is beneficial to postgraduate students and researchers' concerns on recent methods and approaches to kids' cybersecurity.

How can the efficiency of the algorithms be increased with a lesser number of computations as well as optimized with the resources for cost-effective solutions? Artificial Intelligence Techniques for Sustainable Development provides an answer. Further, it discusses important concepts such as green communication network design and implementation for the Internet of Things ecosystem, green computing in network security, and artificial intelligence models for remote sensing applications. Key features: Presents the latest tools and techniques in developing solutions intended for resource utilization, energy efficiency, and human and environmental health Highlights the advancement in electronics and communication technology for green applications Covers smart energy harvesting/charging and power management techniques using machine learning Explains green communication network design and implementation for the Internet of Things ecosystem, and green computing in network security Illustrates prediction models for carbon emission and sequestration, environmental health, and climate change The book is aimed at senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, environmental engineering, and biomedical engineering.

Computational Intelligence for Medical Internet of Things (MIoT) Applications: Machine Intelligence Applications for IoT in Healthcare explores machine intelligence techniques necessary for effective MIoT research and practice, taking a practical approach for practitioners and students entering the field. This book investigates advanced concepts and applications in the MIoT field, guiding readers through emerging developments and future trends. A wide range of international authors guide readers through advanced concepts, including deep learning, neural network, and big data analytic approaches for the classification, indexing, retrieval, analysis, and inferencing of healthcare data. - Presents the state-of-the-art in machine intelligence and related technologies and methodologies for IoT in healthcare - Discusses emerging developments and trends in machine intelligence for business and decision-making strategy in healthcare - Features new models, practical solutions, prototypes, frameworks and technological advances related to machine intelligence for MIoT applications

The world is addressing the insistent challenge of climate change, and the need for innovative solutions has become paramount. In this period of technical developments, artificial intelligence (AI) has emerged as a powerful instrument with enormous prospects to combat climate change and other environmental subjects. AI's ability to process vast amounts of data, identify patterns, and make intelligent predictions offers unprecedented opportunities to tackle this global crisis. High-Performance Computing (HPC) or super-computing environments address these large and complex challenges with individual nodes (computers) working together in a cluster (connected group) to perform massive amounts of computing in a short period. Creating and removing these clusters is often automated in the cloud to reduce costs. Computer networks, communication systems, and other IT infrastructures have a growing environmental footprint due to significant energy consumption and greenhouse gas emissions. To address this seemingly self-defeating conundrum, and create a truly sustainable environment, new energy models, algorithms, methodologies, platforms, tools, and systems are required to support next-generation computing and communication infrastructures. Harnessing High-Performance Computing and AI for Environmental Sustainability navigates through AI-driven solutions from sustainable agriculture and land management to energy optimization and smart grids. It unveils how AI algorithms can analyze colossal datasets, offering unprecedented insights into climate modeling, weather prediction, and long-term climate trends. Integrating AI-powered optimization algorithms revolutionizes energy systems, propelling the transition towards a low-carbon future by reducing greenhouse gas emissions and enhancing efficiency. This book is ideal for educators, environmentalists, industry professionals, and researchers alike, and it explores the ethical dimensions and policies surrounding AI's contribution to environmental development.

Integrating Intelligence and Sustainability in Supply Chains is a comprehensive research guide that delves into the realm of sustainable and smart supply chains. With a focus on bridging the gap between intelligence and sustainability, this book provides a valuable resource for graduate students in business, management, industrial engineering, and industrial ecology. It serves as a unifying platform for researchers across various domains, including operations management, industrial ecology, industrial strategy, risk management, and life cycle assessment, who are passionate about sustainable and smart supply chains. This book offers a wealth of groundbreaking insights from renowned scholars and field experts. It serves as a theoretical and conceptual foundation for environmental researchers seeking a business, policy, or industry perspective. By addressing the key issues at the intersection of operations management and environmental and social responsibility, the book presents a novel approach to mitigating negative impacts and aligning logistics with sustainability and digitalization requirements. Structured in a modular format, this book allows readers to explore specific current topics relevant to their interests. It covers a wide range of subjects, such as measuring environmental impacts, transforming supply chains to meet sustainability challenges, business models for sustainable logistics, and integrative business strategies. Furthermore, the book addresses emerging technologies like big data analytics, artificial intelligence, and the Internet of Things (IoT), exploring their applications in supply chain management.

Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge, facilitated global business, enhanced collaboration, and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression, they also pose significant threats to our privacy. As a result, we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying, with instances of racism, terrorism, and various types of trolling becoming increasingly prevalent worldwide. Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community, particularly within the realm of social media. In this context, artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research, theoretical methods, and novel applications in AI techniques to combat cyberbullying. Discussing new models, practical solutions, and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore, the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly, as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts. Key Features: Proposes new models, practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms. Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence. Includes many case studies and applications of machine intelligence for combating cyberbullying.

In today's world, sustainability is no longer just a buzzword; it is a fundamental concern for businesses seeking to thrive. Traditional marketing strategies often fall short of aligning with the values and expectations of today's socially conscious consumers. Marketers are grappling with the issue of reconciling traditional marketing with the demands of the modern, environmentally conscious consumers. The marketing landscape is rapidly evolving, and businesses are challenged to embrace sustainability while leveraging transformative digital technologies. Smart and Sustainable Interactive Marketing is designed to address this very challenge. This book recognizes this issue as the first step toward its resolution. It delves into the intricate dimensions and features of sustainable marketing, shedding light on how it can harmonize with the contemporary economy and the principles of sustainable development. The book identifies the need for transformation and integration of digital technologies, such as artificial intelligence, to bridge the gap between traditional marketing and sustainability.

Handbook of Green Engineering Technologies for Sustainable Smart Cities focuses on the complete exploration and presentation of green smart city applications, techniques, and architectural frameworks. It provides detailed coverage of urban sustainability spanning across various engineering disciplines. The book discusses and explores green engineering technologies for smart cities and covers various engineering disciplines and environmental science. It emphasizes techniques, application frameworks, tools, and case studies. All chapters play a part in the evolution of sustainable green smart cities and present how to solve environmental issues by applying modern industrial IoT solutions. This book will benefit researchers, smart city practitioners, academicians, university students, and policy makers.

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.